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Null hypothesis
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For the publication, see Null Hypothesis: The Journal of Unlikely Science.
Ronald Fisher
Jerzy Neyman
In inferential statistics, the term "null hypothesis" is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups.[1] Rejecting or disproving the null hypothesis—and thus concluding that there are grounds for believing that there is a relationship between two phenomena (e.g. that a potential treatment has a measurable effect)—is a central task in the modern practice of science; the field of statistics gives precise criteria for rejecting a null hypothesis[citation needed].
The null hypothesis is generally assumed to be true until evidence indicates otherwise. In statistics, it is often denoted H0 (read “H-nought”, "H-null", "H-oh", or "H-zero").
The concept of a null hypothesis is used differently in two approaches to statistical inference. In the significance testing approach of Ronald Fisher, a null hypothesis is rejected if the observed data are significantly unlikely to have occurred if the null hypothesis were true. In this case the null hypothesis is rejected and an alternative hypothesis is accepted in its place. If the data are consistent with the null hypothesis, then the null hypothesis is not rejected. In neither case is the null hypothesis or its alternative proven; the null hypothesis is tested with data and a decision is made based on how likely or unlikely the data are. This is analogous to the legal principle of presumption of innocence, in which a suspect or defendant is assumed to be innocent (null is not rejected) until proven guilty (null is rejected) beyond a reasonable doubt (to a statistically significant degree).
In the hypothesis testing approach of Jerzy Neyman and Egon Pearson, a null hypothesis is contrasted with an alternative hypothesis and the two hypotheses are distinguished on the basis of data, with certain error rates.
Proponents of each approach criticize the other approach. Nowadays, though, a hybrid approach is widely practiced and presented in textbooks. The hybrid is in turn criticized as incorrect and incoherent—for details, see Statistical hypothesis testing.
Statistical inference can be done without a null hypothesis, by specifying a statistical model corresponding to each candidate hypothesis and using model selection techniques to choose the most appropriate model.[2] (The most common selection techniques are based on either Akaike information criterion or Bayes factor.)
Contents
[hide]
1 Principle
2 Basic definitions
3 Example
4 Terminology
5 Goals of null hypothesis tests
6 Choice of the null hypothesis
6.1 Directionality
6.1.1 Tailedness of the null-hypothesis test
6.1.2 Discussion
7 History of statistical tests
8 See also
9 References
10 Further reading
11 External links
Principle[edit]
Hypothesis testing requires constructing a statistical model of what the data would look like, given that chance or random processes alone were responsible for the results. The hypothesis that chance alone is responsible for the results is called the null hypothesis. The model of the result of the random process is called the distribution under the null hypothesis. The obtained results are then compared with the distribution under the null hypothesis, and the likelihood of finding the obtained results is thereby determined.[3]
Hypothesis testing works by collecting data and measuring how likely the particular set of data is, assuming the null hypothesis is true, when the study is on a randomly selected representative sample. The null hypothesis assumes no relationship between variables in the population from which the sample is selected.
If the data-set of a randomly selected representative sample is very unlikely relative to the null hypothesis (defined as being part of a class of sets of data that only rarely will be observed), the experimenter rejects the null hypothesis concluding it (probably) is false. This class of data-sets is usually specified via a test statistic which is designed to measure the extent of apparent departure from the null hypothesis. The procedure works by assessing whether the observed departure measured by the test statistic is larger than a value defined so that the probability of occurrence of a more extreme value is small under the null hypothesis (usually in less than either 5% or 1% of similar data-sets in which the null hypothesis does hold).
If the data do not contradict the null hypothesis, then only a weak conclusion can be made: namely, that the observed data set provides no strong evidence against the null hypothesis. In this case, because the null hypothesis could be true or false, in some contexts this is interpreted as meaning that the data give insufficient evidence to make any conclusion; in other contexts it is interpreted as meaning that there is no evidence to support changing from a currently useful regime to a different one.
For instance, a certain drug may reduce the chance of having a heart attack. Possible null hypotheses are "this drug does not reduce the chances of having a heart attack" or "this drug has no effect on the chances of having a heart attack". The test of the hypothesis consists of administering the drug to half of the people in a study group as a controlled experiment. If the data show a statistically significant change in the people receiving the drug, the null hypothesis is rejected.
Basic definitions[edit]
The null hypothesis and the alternate hypothesis are types of conjectures used in statistical tests, which are formal methods of reaching conclusions or making decisions on the basis of data. The hypotheses are conjectures about a statistical model of the population, which are based on a sample of the population. The tests are core elements of statistical inference, heavily used in the interpretation of scientific experimental data, to separate scientific claims from statistical noise.
"The statement being tested in a test of statistical significance is called the null hypothesis. The test of significance is designed to assess the strength of the evidence against the null hypothesis. Usually, the null hypothesis is a statement of 'no effect' or 'no difference'."[4] It is often symbolized as H0.
The statement that is being tested against the null hypothesis is the alternative hypothesis.[4] Symbols include H1 and Ha.
Statistical significance test: "Very roughly, the procedure for deciding goes like this: Take a random sample from the population. If the sample data are consistent with the null hypothesis, then do not reject the null hypothesis; if the sample data are inconsistent with the null hypothesis, then reject the null hypothesis and conclude that the alternative hypothesis is true."[5]
The following sections add context and nuance to the basic definitions.
Example[edit]
Given the test scores of two random samples of men and women, does one group differ from the other? A possible null hypothesis is that the mean male score is the same as the mean female score:
H0: μ1 = μ2
where
H0 = the null hypothesis,
μ1 = the mean of population 1, and
μ2 = the mean of population 2.
A stronger null hypothesis is that the two samples are drawn from the same population, such that the variances and shapes of the distributions are also equal.
Terminology[edit]
Main article: Statistical hypothesis testing § Definition of terms
Simple hypothesis
Any hypothesis which specifies the population distribution completely. For such a hypothesis the sampling distribution of any statistic is a function of the sample size alone.
Composite hypothesis
Any hypothesis which does not specify the population distribution completely. Example: A hypothesis specifying a normal distribution with a specified mean and an unspecified variance.
The simple/composite distinction was made by Neyman and Pearson.[6]
Exact hypothesis
Any hypothesis that specifies an exact parameter value.[7] Example: μ = 100. Synonym: point hypothesis.
Inexact hypothesis
Those specifying a parameter range or interval. Examples: μ ≤ 100; 95 ≤ μ ≤ 105.
Fisher required an exact null hypothesis for testing (see the quotations below).
A one-tailed hypothesis (tested using a one-sided test)[4] is an inexact hypothesis in which the value of a parameter is specified as being either:
above or equal to a certain value, or
below or equal to a certain value.
A one-tailed hypothesis is said to have directionality.
Fisher's original (lady tasting tea) example was a one-tailed test. The null hypothesis was asymmetric. The probability of guessing all cups correctly was the same as guessing all cups incorrectly, but Fisher noted that only guessing correctly was compatible with the lady's claim. (See the quotations below about his reasoning.)
Goals of null hypothesis tests[edit]
There are many types of significance tests for one, two or more samples, for means, variances and proportions, paired or unpaired data, for different distributions, for large and small samples; all have null hypotheses. There are also at least four goals of null hypotheses for significance tests:[8]
Technical null hypotheses are used to verify statistical assumptions. For example, the residuals between the data and a statistical model cannot be distinguished from random noise. If true, there is no justification for complicating the model.
Scientific null assumptions are used to directly advance a theory. For example, the angular momentum of the universe is zero. If not true, the theory of the early universe may need revision.
Null hypotheses of homogeneity are used to verify that multiple experiments are producing consistent results. For example, the effect of a medication on the elderly is consistent with that of the general adult population. If true, this strengthens the general effectiveness conclusion and simplifies recommendations for use.
Null hypotheses that assert the equality of effect of two or more alternative treatments, for example, a drug and a placebo, are used to reduce scientific claims based on statistical noise. This is the most popular null hypothesis; It is so popular that many statements about significant testing assume such null hypotheses.
Rejection of the null hypothesis is not necessarily the real goal of a significance tester. An adequate statistical model may be associated with a failure to reject the null; the model is adjusted until the null is not rejected. The numerous uses of significance testing were well known to Fisher who discussed many in his book written a decade before defining the null hypothesis.[9]
A statistical significance test shares much mathematics with a confidence interval. They are mutually illuminating. A result is often significant when there is confidence in the sign of a relationship (the interval does not include 0). Whenever the sign of a relationship is important, statistical significance is a worthy goal. This also reveals weaknesses of significance testing: A result can be significant without a good estimate of the strength of a relationship; significance can be a modest goal. A weak relationship can also achieve significance with enough data. Reporting both significance and confidence intervals is commonly recommended.
The varied uses of significance tests reduce the number of generalizations that can be made about all applications.
Choice of the null hypothesis[edit]
The choice of the null hypothesis is associated with sparse and inconsistent advice. Fisher mentioned few constraints on the choice and stated that many null hypotheses should be considered and that many tests are possible for each. The variety of applications and the diversity of goals suggests that the choice can be complicated. In many applications the formulation of the test is traditional. A familiarity with the range of tests available may suggest a particular null hypothesis and test. Formulating the null hypothesis is not automated (though the calculations of significance testing usually are). Sir David Cox has said, "How [the] translation from subject-matter problem to statistical model is done is often the most critical part of an analysis".[10]
A statistical significance test is intended to test a hypothesis. If the hypothesis summarizes a set of data, there is no value in testing the hypothesis on that set of data. Example: If a study of last year's weather reports indicates that rain in a region falls primarily on weekends, it is only valid to test that null hypothesis on weather reports from any other year. Testing hypotheses suggested by the data is circular reasoning that proves nothing; It is a special limitation on the choice of the null hypothesis.
A routine procedure is as follows: Start from the scientific hypothesis. Translate this to a statistical alternative hypothesis and proceed: "Because Ha expresses the effect that we wish to find evidence for, we often begin with Ha and then set up H0 as the statement that the hoped-for effect is not present."[4] This advice is reversed for modeling applications where we hope not to find evidence against the null.
A complex case example is as follows:[11] The gold standard in clinical research is the randomized placebo-controlled double-blind clinical trial. But testing a new drug against a (medically ineffective) placebo may be unethical for a serious illness. Testing a new drug against an older medically effective drug raises fundamental philosophical issues regarding the goal of the test and the motivation of the experimenters. The standard "no difference" null hypothesis may reward the pharmaceutical company for gathering inadequate data. "Difference" is a better null hypothesis in this case, but statistical significance is not an adequate criterion for reaching a nuanced conclusion which requires a good numeric estimate of the drug's effectiveness. A "minor" or "simple" proposed change in the null hypothesis ((new vs old) rather than (new vs placebo)) can have a dramatic effect on the utility of a test for complex non-statistical reasons.
Directionality[edit]
Main article: One- and two-tailed tests
This section is too long. Consider splitting it into new pages, adding subheadings, or condensing it. (September 2014)
The choice of null hypothesis (H0) and consideration of directionality (see "one-tailed test") is critical.
Tailedness of the null-hypothesis test[edit]
Consider the question of whether a tossed coin is fair (i.e. that on average it lands heads up 50% of the time) and an experiment where you toss the coin 5 times. A possible result of the experiment that we consider here is 5 heads. Let outcomes be considered unlikely with respect to an assumed distribution if their probability is lower than a significance threshold of 0.05.
A potential null hypothesis implying a one-tail test is "this coin is not biased toward heads". Beware that, in this context, the word "tail" takes two meanings: either as outcome of a single toss, or as region of extremal values in a probability distribution.
Indeed, with a fair coin the probability of this experiment outcome is 1/25=0.031, which would be even lower if the coin were biased in favour of tails. Therefore, the observations are not likely enough for the null hypothesis to hold, and the test refutes it. Since the coin is ostensibly neither fair nor biased toward tails, the conclusion of the experiment is that the coin is biased towards heads.
Alternatively, a null hypothesis implying a two-tailed test is "this coin is fair". This one null hypothesis could be examined by looking out for either too many tails or too many heads in the experiments. The outcomes that would tend to refuse this null hypothesis are those with a large number of heads or a large number of tails, and our experiment with 5 heads would seem to belong to this class.
However, the probability of 5 tosses of the same kind, irrespective of whether these are head or tails, is twice as much as that of the 5-head occurrence singly considered. Hence, under this two-tailed null hypothesis, the observation receives a probability value of 0.063. Hence again, with the same significance threshold used for the one-tailed test (0.05), the same outcome is not statistically significant. Therefore, the two-tailed null hypothesis will be preserved in this case, not supporting the conclusion reached with the single-tailed null hypothesis, that the coin is biased towards heads.
This example illustrates that the conclusion reached from a statistical test may depend on the precise formulation of the null and alternative hypotheses.
Discussion[edit]
Fisher said, "the null hypothesis must be exact, that is free of vagueness and ambiguity, because it must supply the basis of the 'problem of distribution,' of which the test of significance is the solution", implying a more restrictive domain for H0.[12] According to this view, the null hypothesis must be numerically exact—it must state that a particular quantity or difference is equal to a particular number. In classical science, it is most typically the statement that there is no effect of a particular treatment; in observations, it is typically that there is no difference between the value of a particular measured variable and that of a prediction.
Most statisticians believe that it is valid to state direction as a part of null hypothesis, or as part of a null hypothesis/alternative hypothesis pair.[13] However, the results are not a full description of all the results of an experiment, merely a single result tailored to one particular purpose. For example, consider an H0 that claims the population mean for a new treatment is an improvement on a well-established treatment with population mean = 10 (known from long experience), with the one-tailed alternative being that the new treatment's mean > 10. If the sample evidence obtained through x-bar equals −200 and the corresponding t-test statistic equals −50, the conclusion from the test would be that there is no evidence that the new treatmnent is better than the existing one: it would not report that it is markedly worse, but that is not what this particular test is looking for. To overcome any possible ambiguity in reporting the result of the test of a null hypothesis, it is best to indicate whether the test was two-sided and, if one-sided, to include the direction of the effect being tested.
The statistical theory required to deal with the simple cases of directionality dealt with here, and more complicated ones, makes use of the concept of an unbiased test.
The directionality of hypotheses is not always obvious. The explicit null hypothesis of Fisher's Lady tasting tea example was that the Lady had no such ability, which led to a symmetric probability distribution. The one-tailed nature of the test resulted from the one-tailed alternate hypothesis (a term not used by Fisher). The null hypothesis became implicitly one-tailed. The logical negation of the Lady's one-tailed claim was also one-tailed. (Claim: Ability > 0; Stated null: Ability = 0; Implicit null: Ability ≤ 0).
Pure arguments over the use of one-tailed tests are complicated by the variety of tests. Some tests (for instance the χ2 goodness of fit test) are inherently one-tailed. Some probability distributions are asymmetric. The traditional tests of 3 or more groups are two-tailed.
Advice concerning the use of one-tailed hypotheses has been inconsistent and accepted practice varies among fields.[14] The greatest objection to one-tailed hypotheses is their potential subjectivity. A non-significant result can sometimes be converted to a significant result by the use of a one-tailed hypothesis (as the fair coin test, at the whim of the analyst). The flip side of the argument: One-sided tests are less likely to ignore a real effect. One-tailed tests can suppress the publication of data that differs in sign from predictions. Objectivity was a goal of the developers of statistical tests.
It is a common practice to use a one-tailed hypotheses by default. However, "If you do not have a specific direction firmly in mind in advance, use a two-sided alternative. Moreover, some users of statistics argue that we should always work with the two-sided alternative."[4][15]
One alternative to this advice is to use three-outcome tests. It eliminates the issues surrounding directionality of hypotheses by testing twice, once in each direction and combining the results to produce three possible outcomes.[16] Variations on this approach have a history, being suggested perhaps 10 times since 1950.[17]
Disagreements over one-tailed tests flow from the philosophy of science. While Fisher was willing to ignore the unlikely case of the Lady guessing all cups of tea incorrectly (which may have been appropriate for the circumstances), medicine believes that a proposed treatment that kills patients is significant in every sense and should be reported and perhaps explained. Poor statistical reporting practices have contributed to disagreements over one-tailed tests. Statistical significance resulting from two-tailed tests is insensitive to the sign of the relationship; Reporting significance alone is inadequate. "The treatment has an effect" is the uninformative result of a two-tailed test. "The treatment has a beneficial effect" is the more informative result of a one-tailed test. "The treatment has an effect, reducing the average length of hospitalization by 1.5 days" is the most informative report, combining a two-tailed significance test result with a numeric estimate of the relationship between treatment and effect. Explicitly reporting a numeric result eliminates a philosophical advantage of a one-tailed test. An underlying issue is the appropriate form of an experimental science without numeric predictive theories: A model of numeric results is more informative than a model of effect signs (positive, negative or unknown) which is more informative than a model of simple significance (non-zero or unknown); in the absence of numeric theory signs may suffice.
History of statistical tests[edit]
Main article: Statistical hypothesis testing § Origins and early controversy
The history of the null and alternative hypotheses is embedded in the history of statistical tests.[18][19]
Before 1925: There are occasional transient traces of statistical tests for centuries in the past, which provide early examples of null hypotheses. In the late 19th century statistical significance was defined. In the early 20th century important probability distributions were defined. Gossett and Pearson worked on specific cases of significance testing.
1925: Fisher published the first edition of Statistical Methods for Research Workers which defined the statistical significance test and made it a mainstream method of analysis for much of experimental science. The text was devoid of proofs and weak on explanations, but it was filled with real examples. It placed statistical practice in the sciences well in advance of published statistical theory.
1933: In a series of papers (published over a decade starting in 1928) Neyman & Pearson defined the statistical hypothesis test as a proposed improvement on Fisher's test. The papers provided much of the terminology for statistical tests including alternative hypothesis and H0 as a hypothesis to be tested using observational data (with H1, H2... as alternatives).[6] Neyman did not use the term null hypothesis in later writings about his method.
1935: Fisher published the first edition of the book "The Design of Experiments" which introduced the null hypothesis[20] (by example rather than by definition) and carefully explained the rationale for significance tests in the context of the interpretation of experimental results; see The Design of Experiments#Quotations regarding the null hypothesis.
Following: Fisher and Neyman quarreled over the relative merits of their competing formulations until Fisher's death in 1962. Career changes and World War II ended the partnership of Neyman and Pearson. The formulations were merged by relatively anonymous textbook writers, experimenters (journal editors) and mathematical statisticians without input from the principals.[18] The subject today combines much of the terminology and explanatory power of Neyman & Pearson with the scientific philosophy and calculations provided by Fisher. Whether statistical testing is properly one subject or two remains a source of disagreement.[21] Sample of two: One text refers to the subject as hypothesis testing (with no mention of significance testing in the index) while another says significance testing (with a section on inference as a decision). Fisher developed significance testing as a flexible tool for researchers to weigh their evidence. Instead testing has become institutionalized. Statistical significance has become a rigidly defined and enforced criterion for the publication of experimental results in many scientific journals. In some fields significance testing has become the dominant and nearly exclusive form of statistical analysis. As a consequence the limitations of the tests have been exhaustively studied. Books have been filled with the collected criticism of significance testing.
See also[edit]
Statistics portal
Bayes factor
Burden of proof
Counternull
Estimation statistics
Likelihood-ratio test
Presumption of innocence
Statistical hypothesis testing
References[edit]
Jump up ^ Everitt, Brian (1998). The Cambridge Dictionary of Statistics. Cambridge, UK New York: Cambridge University Press. ISBN 0521593468.
Jump up ^ Burnham, K. P.; Anderson, D. R. (2002), Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed.), Springer-Verlag, ISBN 0-387-95364-7 .
Jump up ^ Stockburger D.W. (2007), "Hypothesis and hypothesis testing", Encyclopedia of Measurement and Statistics (editor—Salkind N.J.), Sage Publications.
^ Jump up to: a b c d e Moore, David; McCabe, George (2003). Introduction to the Practice of Statistics (4 ed.). New York: W.H. Freeman and Co. p. 438. ISBN 9780716796572.
Jump up ^ Weiss, Neil A. (1999). Introductory Statistics (5th ed.). p. 494. ISBN 9780201598773.
^ Jump up to: a b Neyman, J; Pearson, E. S. (January 1, 1933). "On the Problem of the most Efficient Tests of Statistical Hypotheses". Philosophical Transactions of the Royal Society A. 231 (694–706): 289–337. doi:10.1098/rsta.1933.0009.
Jump up ^ Winkler, Robert L; Hays, William L (1975). Statistics : probability, inference, and decision. New York: Holt, Rinehart and Winston. p. 403. ISBN 0-03-014011-0.
Jump up ^ "Statistical Significance Tests". Br. J. Clin. Pharmacol. 14: 325–331. 1982.
Jump up ^ Statistical Methods for Research Workers (11th Ed): Chapter IV: Tests of Goodness of Fit, Independence and Homogeneity; With Table of χ2. Regarding a significance test supporting goodness of fit: If the calculated probability is high then "there is certainly no reason to suspect that the [null] hypothesis is tested. If it is [low] it is strongly indicated that the [null] hypothesis fails to account for the whole of the facts."
Jump up ^ Cox, D. R. (2006). Principles of Statistical Inference. Cambridge University Press. p. 197. ISBN 0-521-68567-2.
Jump up ^ Jones, B; P Jarvis; J A Lewis; A F Ebbutt (6 July 1996). "Trials to assess equivalence: the importance of rigorous methods". BMJ. 313: 36–39. doi:10.1136/bmj.313.7048.36. It is suggested that the default position (the null hypothesis) should be that the treatments are not equivalent. Conclusions should be made on the basis of confidence intervals rather than significance.
Jump up ^ Fisher, R. A. (1966). The Design of Experiments (8th ed.). Edinburgh: Hafner.
Jump up ^ For example see Null hypothesis
Jump up ^ Lombardi, Celia M.; Hurlbert, Stuart H. (2009). "Misprescription and misuse of one-tailed tests". Austral Ecology. 34: 447–468. doi:10.1111/j.1442-9993.2009.01946.x. Discusses the merits and historical usage of one-tailed tests in biology at length.
Jump up ^ Bland, J Martin; Altman, Douglas G (23 July 1994). "One and two sided tests of significance". BMJ. 309: 248. doi:10.1136/bmj.309.6949.248. With respect to medical statistics: "In general a one sided test is appropriate when a large difference in one direction would lead to the same action as no difference at all. Expectation of a difference in a particular direction is not adequate justification." "Two sided tests should be used unless there is a very good reason for doing otherwise. If one sided tests are to be used the direction of the test must be specified in advance. One sided tests should never be used simply as a device to make a conventionally non-significant difference significant."
Jump up ^ Jones, Lyle V.; Tukey, John W. (2000). "A Sensible Formulation of the Significance Test". Psychological Methods. 5 (4): 411–414. doi:10.1037/1082-989X.5.4.411. Test results are signed: significant positive effect, significant negative effect or insignificant effect of unknown sign. This is a more nuanced conclusion than that of the two-tailed test. It has the advantages of one-tailed tests without the disadvantages.
Jump up ^ Hurlbert, S. H.; Lombardi, C. M. (2009). "Final collapse of the Neyman-Pearson decision theoretic framework and rise of the neoFisherian". Ann. Zool. Fennici. 46: 311–349. doi:10.5735/086.046.0501. ISSN 1797-2450.
^ Jump up to: a b Gigerenzer, Gerd; Zeno Swijtink; Theodore Porter; Lorraine Daston; John Beatty; Lorenz Kruger (1989). "Part 3: The Inference Experts". The Empire of Chance: How Probability Changed Science and Everyday Life. Cambridge University Press. pp. 70–122. ISBN 978-0-521-39838-1.
Jump up ^ Lehmann, E. L. (2011). Fisher, Neyman, and the creation of classical statistics. New York: Springer. ISBN 978-1441994998.
Jump up ^ Aldrich, John. "Earliest Known Uses of Some of the Words of Probability & Statistics". Retrieved 30 June 2014. Last update 12 march 2003. From Jeff Miller.
Jump up ^ Lehmann, E. L. (December 1993). "The Fisher, Neyman-Pearson Theories of Testing Hypotheses: One Theory or Two?". Journal of the American Statistical Association. 88 (424): 1242–1249. doi:10.1080/01621459.1993.10476404.
Further reading[edit]
Adèr, H. J.; Mellenbergh, G. J. & Hand, D. J. (2007). Advising on research methods: A consultant's companion. Huizen, The Netherlands: Johannes van Kessel Publishing. ISBN 90-79418-01-3.
Efron, B. (2004). "Large-Scale Simultaneous Hypothesis Testing". Journal of the American Statistical Association. 99 (465): 96. doi:10.1198/016214504000000089. The application of significance testing in this paper is an outlier. Tests to find a null hypothesis? Not trying to show significance, but to find interesting cases?
Rice, William R.; Gaines, Steven D. (June 1994). "'Heads I win, tails you lose': testing directional alternative hypotheses in ecological and evolutionary research". TREE. 9 (6): 235–237. doi:10.1016/0169-5347(94)90258-5. Directed tests combine the attributes of one-tailed and two-tailed tests. "...directed tests should be used in virtually all applications where one-sided tests have previously been used, excepting those cases where the data can only deviate from H0, in one direction."
External links[edit]
HyperStat Online: Null hypothesis
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Help
Category:Hurricanes in Costa Rica
From Wikipedia, the free encyclopedia
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These hurricanes all affected Costa Rica.
Pages in category "Hurricanes in Costa Rica"
The following 12 pages are in this category, out of 12 total. This list may not reflect recent changes (learn more).
0–9
Tropical Depression Twelve-E (2011)
1887 Atlantic hurricane season
1906 Florida Keys hurricane
A
Tropical Storm Alma
B
Hurricane Beta
C
Hurricane Cesar–Douglas
G
Hurricane Gert
I
Hurricane Ida
M
Hurricane Martha
N
Hurricane Nate (2017)
O
Hurricane Otto
P
Hurricane Patricia
Retrieved from "https://en.wikipedia.org/w/index.php?title=Category:Hurricanes_in_Costa_Rica&oldid=589841538"
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Hurricanes in Central America
Natural disasters in Costa Rica
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James Remar
From Wikipedia, the free encyclopedia
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James Remar
Remar at the 2010 Screen Actors Guild Awards
Born
William James Remar
(1953-12-31) December 31, 1953 (age 64)
Boston, Massachusetts, U.S.
Occupation
Actor, voice actor
Years active
1978–present
William James Remar (born December 31, 1953) is an American actor and voice actor. He played Richard, the on-off tycoon boyfriend of Kim Cattrall's character in Sex and the City, Ajax in The Warriors (1979),[1] homicidal maniac Albert Ganz in the thriller 48 Hrs. (1982), gangster Dutch Schultz in The Cotton Club (1984), Lord Raiden in Mortal Kombat: Annihilation (1997), Jack Duff in Miracle on 34th Street (1994), and Harry Morgan in the Showtime TV series Dexter. Since 2009, he has done voiceover work in ads for Lexus luxury cars.[2] Remar studied acting at The Neighborhood Playhouse School of the Theatre in New York City.
Contents
[hide]
1 Early life
2 Career
2.1 Films
2.2 Television
3 Filmography
3.1 Film
3.2 Television
3.3 Video games
4 References
5 External links
Early life[edit]
Remar was born in Boston, Massachusetts, the son of Elizabeth Mary, a mental health state official originally from West Kirby, England, and S. Roy Remar, an attorney. His paternal grandparents were Russian Jewish immigrants (the family name was originally "Remarman").[citation needed]
Career[edit]
Films[edit]
Remar has spent the majority of his film career playing villains. He portrayed the violent and sexually aggressive character Ajax in the cult film The Warriors (1979), and the murdering sociopath Albert Ganz in the hit 48 Hrs. (1982). (Both films were directed by Walter Hill and co-starred David Patrick Kelly, whose character is named Luther in both). Remar also played real-life 1930s-era gangster Dutch Schultz in The Cotton Club (1984).
In contrast to these roles, Remar starred in the film Windwalker (1980) as the young Cheyenne Windwalker, for which he spoke his lines in the Cheyenne language. He also portrayed a gay man in the film Cruising (1980). In the same year, Remar had a cameo in the Western The Long Riders (1980); his character faced David Carradine's character in a bar fight over a woman Remar's character was married to.
He was the star of the 1986 film Quiet Cool (1986) and was cast as Corporal Hicks in the science-fiction/horror film Aliens (1986), but was replaced by Michael Biehn shortly after filming began, due to Remar's having a drug problem. For several years, the reason behind his dismissal was reported as "creative differences" with director James Cameron.[3] At least one piece of footage featuring Remar made it into the final version of the film: when the Marines enter the processing station, and the camera tilts down from the Alien nest, though Remar is not seen in close-up.[4] He is also filmed from the back as the Marines first enter the compound on LV-426 and when "Hicks" approaches the cocooned woman, again filmed from the rear so the viewer is unable to tell it is Remar and not Michael Biehn.[citation needed]
He played Quill, one of the main villains in The Phantom (1996). He appeared in Mortal Kombat: Annihilation (1997), the sequel to the film Mortal Kombat (1995), taking over the role of Raiden from Christopher Lambert. He then followed this with a role in the direct-to-video science fiction movie Robo Warriors (1996). Other films include Psycho (1998), in which he played the patrolman, Drugstore Cowboy (1989), Tales from the Darkside: The Movie (1990), Wedlock (1991), Boys on the Side (1995), The Quest (1996), Rites of Passage (1999), Hellraiser: Inferno (2000), 2 Fast 2 Furious (2003), Fear X (2003), Blade: Trinity (2004), The Girl Next Door (2004). He played a brief role as General Bratt in the prologue of Pineapple Express (2008). He also had a role in the horror movie The Unborn (2009), alongside C.S. Lee, who portrays Vince Masuka in Dexter).
Remar was featured in the film X-Men: First Class (2011) and voiced the Autobot Sideswipe in the film Transformers: Dark of the Moon (2011), replacing André Sogliuzzo. He was also cast in the heist film Setup (2011) and starred in the film Arena (2011).
Remar played two different, unrelated characters in Quentin Tarantino's film Django Unchained (2012):[5] his first character, Ace Speck, is killed near the beginning of the film by lead character, King Schultz (played by Christoph Waltz); Remar's second character, Butch Pooch, kills King Schultz near the end of the film. He starred, alongside Emma Roberts, Lucy Boynton, and Lauren Holly, in the thriller film The Blackcoat's Daughter (2015).[6]
Television[edit]
Remar's television appearances include the series Miami Vice, Hill Street Blues, Sex and the City (as the on-again, off-again boyfriend of Kim Cattrall's character), Tales from the Crypt, Jericho, Third Watch, Justice League Unlimited, and Battlestar Galactica. He also appeared as a possessed mental patient in The X-Files ninth-season episode "Daemonicus". He starred as Tiny Bellows on the short-lived television series, The Huntress (2000–2001). He appeared in the miniseries The Grid (2004) as Hudson "Hud", the love interest of Julianna Margulies' character. He had a recurring guest role in the 2006 television series Jericho on CBS. Remar guest-starred in the CBS crime drama Numbers, playing a weapons dealer who later turns good and helps the FBI.
From 2006 to 2013, Remar co-starred in Dexter on Showtime. Remar was nominated for a Saturn Award for Best Supporting Actor for his portrayal of Dexter Morgan's adoptive father, Harry Morgan.[7]
In 2010, he played guest roles as Giuseppe Salvatore in The CW series The Vampire Diaries[8] and as James Ermine, a general for Jericho, a black-ops military contractor, on FlashForward.
He also voiced Vilgax in the animated television series Ben 10: Alien Force and Ben 10: Ultimate Alien, replacing Steve Blum. He guest-starred in Private Practice in 2010, playing a physician named Gibby who works with Doctors Without Borders.[9] On July 23, 2017 Remar was subsequently cast as Peter Gambi on the superhero drama Black Lightning.[10]
Filmography[edit]
Film[edit]
Year
Title
Role
Notes
1978 On the Yard Larson
1979 The Warriors Ajax
1979 Blond Poison N/A
1980 Cruising Gregory
1980 The Long Riders Sam Starr
1980 Windwalker Young Windwalker
1982 Partners Edward K. Petersen
1982 48 Hrs. Albert Ganz
1984 The Cotton Club Dutch Schultz
1986 The Clan of the Cave Bear Creb
1986 Band of the Hand Nestor
1986 Quiet Cool Joe Dylanne
1987 Rent-A-Cop Dancer
1989 The Dream Team Gianelli
1989 Silent Like Glass Charly
1989 Drugstore Cowboy Gentry
1990 Tales from the Darkside: The Movie Preston segment: "Lover's Vow"
1991 White Fang Beauty Smith
1991 Wedlock Sam
1992 The Tigress Andrei
1993 Fatal Instinct Max Shady
1994 Blink Thomas Ridgely
1994 Confessions of a Hitman Bruno Serrano
1994 Renaissance Man Captain Tom Murdoch
1994 Miracle on 34th Street Jack Duff
1995 The Surgeon Dr. Benjamin Hendricks
1995 Boys on the Side Alex
1995 Across the Moon Rattlesnake Jim
1995 Judge Dredd Block Warlord character name in Judge dredd was Monroe
1995 Wild Bill Donnie Lonigan
1996 One Good Turn Simon Jury
1996 The Quest Maxie Devine
1996 The Phantom Quill
1996 Robo Warriors Ray Gibson
1997 Mortal Kombat: Annihilation Lord Raiden
1998 Psycho Patrolman
1999 Born Bad Sheriff Larabee
1999 Rites of Passage Frank Dabbo
2000 Blowback John Matthew Whitman / Schmidt
2000 What Lies Beneath Warren Feur
2000 The Base 2: Guilty as Charged Lt. Col. Strauss
2000 Hellraiser: Inferno Dr. Paul Gregory
2000 Double Frame Det. Tim Follett
2001 Guardian Detective Carpenter
2001 Dying on the Edge Jackie James
2003 Down with the Joneses Vic
2003 Fear X Peter
2003 Betrayal Alex Tyler
2003 2 Fast 2 Furious Agent Markham
2003 Duplex Chick
2004 The Girl Next Door Hugo Posh
2004 Blade: Trinity Ray Cumberland
2007 Ratatouille Larousse Voice role
2008 Pineapple Express General Bratt
2009 The Unborn Gordon Beldon
2009 2B Tom Mortlake
2009 Endless Bummer Sam Kramer
2010 Gun Detective Rogers
2010 Red Gabriel Singer
2011 The FP Narrator Voice role
2011 X-Men: First Class U.S. General
2011 Transformers: Dark of the Moon Sideswipe Voice role
2011 Setup William Long
2011 Arena Agent McCarty
2011 Vs Rickshaw
2012 Django Unchained Butch Pooch / Ace Speck
2013 Horns Derrick Perrish
2014 Persecuted John Luther
2014 Eden Coach DaFoe
2014 Lap Dance Patrick Moore
2015 The Blackcoat's Daughter Bill
2015 Papa Hemingway in Cuba Santo Trafficante Jr.
2016 Decommissioned David Marino
2016 Unnatural Martin Nakos
2016 The Dog Lover Daniel Holloway
2016 The Land Before Time: Journey of the Heart Topsy Voice role
2016 USS Indianapolis: Men of Courage Admiral Parnell
2017 The Saint Arnold Valecross
2017 Feed Tom
Television[edit]
Year
Title
Role
Notes
1981 Hill Street Blues Cooper Episode: "Rites of Spring"
1984 The Mystic Warrior Pesla Television film
1985 Miami Vice Robbie Cann Episode: "Buddies"
1987 The Equalizer Tremayne Episode: "High Performance"
1987 Deadly Nightmares Ron Episode: "Homebodies"
1987 Crime Story Smilin' Jack Episode: "Blast from the Past"
1989 Desperado: The Outlaw Wars John Sikes Television film
1990 Kojak: None So Blind Wolfgang Reiger Television film
1990 Night Visions Sergeant Thomas Mackey Television film
1991 Session Man McQueen Television film
1991 Tales from the Crypt Red Buckley Episode: "Dead Wait"
1991 Brotherhood of the Gun Frank Weir Television film
1992 Strangers Bernard Television film
1992 Indecency Mick Clarkson Television film
1996 Cutty Whitman Cutty Whitman Television film
1997 Total Security Frank Cisco Main Role
1998 Inferno Dr. Coleman West Television film
1999 Walker, Texas Ranger Keith Bolt Episode: "The Principal"
2000 18 Wheels of Justice Mitch Davis / "Gabriel" Episode: "Wages of Sin"
2001 7th Heaven James Carver 2 episodes
2001 The Huntress Tiny Bellows Main role; 28 episodes
2001 Strong Medicine Guy Falls Episode: "Systemic"
2001 The X-Files Josef Kobold Episode: "Dæmonicus"
2001–2006 Justice League/Justice League Unlimited Hawkman/Carter Hall
Shadow Thief
Lead Manhunter Voice role; 4 episodes
2002 The Twilight Zone Alois Hitler Episode: "Cradle of Darkness"
2002 Third Watch Det. Madjanski 4 episodes
2002–2004 Sex and the City Richard Wright Recurring role; 12 episodes
2003 Peacemakers Cole Hawkins Episode: "Legend of the Gun"
2003 Without a Trace Lucas Vohland Episode: "Confidence"
2004 The Grid Hudson "Hud" Benoit Miniseries
2004 The Survivors Club Roan Griffin Television film
2004 Ike: Countdown to D-Day Gen. Omar Bradley Television film
2004 Meltdown Colonel Boggs Television film
2005 Battlestar Galactica Meier 2 episodes
2006 CSI: Miami Capt. Quentin Taylor Episode: "Open Water"
2006 Thief Agent Patterson Miniseries
2006–2007 Eli Stone Salinsky Episode: "Praying for Time"
2006–2007 Jericho Jonah Prowse Recurring role; 5 episodes
2006–2008 The Batman Black Mask Voice role; 3 episodes
2006–2013 Dexter Harry Morgan Main role; 96 episodes
2007 Sharpshooter Dillon Television film
2009 The Unit Reece Episode: "Hero"
2009 Criminal Minds Tom Benton Episode: "Demonology"
2009 The Spectacular Spider-Man Walter Hardy / Cat Burglar Voice role; episode: "Opening Night"
2009–2010 Batman: The Brave and the Bold Two-Face Voice role; 2 episodes
2009–2010 Ben 10: Alien Force Vilgax, Additional Voices Recurring role
2009 The Christmas Hope Mark Addison Television film
2010 D.R.E.A.M. Team Shawn Murphy Television film
2010 FlashForward James Ermine Episode: "Blowback"
2010 The Vampire Diaries Giuseppe Salvatore 2 episodes
2010 Private Practice Gibby Episode: "Playing God"
2011 Human Target Warden Cole Episode: "Warden Cole"
2011 Hawaii Five-0 Elliott Connor Episode: "Ua Hiki Mai Kapalena Pau"
2011 Young Justice Joar Mahkent / Icicle Sr. / Wilcox Voice role; episode: "Terrors"
2011 Pound Puppies Sarge Voice role; episode: "The K9 Kid"
2011–2012 Ben 10: Ultimate Alien Vilgax / Ultimate Vilgax Recurring role
2013 Hatfields & McCoys Joe Hatfield Miniseries
2013–2014 Beware the Batman Silver Monkey / Mr. Reese (voice) 3 episodes
2013–2014 The Legend of Korra Tonraq (voice) 14 episodes
2013–2014 Grey's Anatomy James Evans Recurring role; 6 episodes
2013–2014 Wilfred Henry Newman 5 episodes
2014 From Dusk Till Dawn: The Series Gecko Father Episode: "Boxman"
2016 The Shannara Chronicles Cephalo Recurring role; 7 episodes
2017 Gotham Frank Gordon 3 episodes
2017 NCIS: Los Angeles Admiral Sterling Bridges 2 episodes
2017 The Path Kodiak Recurring role; 8 episodes
2018 Black Lightning Peter Gambi Series Regular
Video games[edit]
Year
Title
Role
2005 The Warriors Ajax
2010 Batman: The Brave and the Bold – The Videogame Two-Face
2011 Killzone 3 Captain Jason Narville
2014 Destiny Executor Hideo, New Monarchy Merchant[11]
2017 Destiny 2 Executor Hideo
References[edit]
Jump up ^ Maslin, Janet (February 10, 1979). "The Warriors (1979) Movie: 'Warriors' Creates Visual Style That Is Stark: The Cast". The New York Times.
Jump up ^ Barry, Keith (2009-03-16). "Lexus Pursues a New Pitchman". Wired. Retrieved 2017-02-07.
Jump up ^ "SiDEBAR Podcast Episode 128: 'Dexter' Star JAMES REMAR Gets in Character". 2012. Archived from the original on 2014-11-29.
Jump up ^ Making of Aliens. 2003.
Jump up ^ "Django Unchained". The New York Times.
Jump up ^ "James Remar Gets Possessed In 'February'". The New York Times.
Jump up ^ "Paleyfest 2010: Dexter Panel Reveals a Few Clues for Season Five".
Jump up ^ Keck, William (November 20, 2009). "Dexter's Dad Does Vampire Diaries". TV Guide Magazine. Archived from the original on May 20, 2010. Retrieved May 17, 2010.
Jump up ^ "James Remar to star in Private Practice season 4". Archived from the original on 2010-08-06.
Jump up ^ Petski, Denise (July 23, 2017). "'Black Lightning' Casts James Remar & Damon Gupton As Series Regulars, Watch Trailer – Comic-Con". Deadline.com.
Jump up ^ Destiny - End Credits - IGN Video. IGN Video. 2014-09-11. Retrieved 2014-12-04.
External links[edit]
Wikimedia Commons has media related to James Remar.
James Remar on IMDb
Authority control
WorldCat Identities
VIAF: 56809780
LCCN: n85376696
ISNI: 0000 0001 0654 4242
GND: 13602534X
SUDOC: 119011980
BNF: cb14028732m (data)
BIBSYS: 3006898
SNAC: w6gt6cmb
Retrieved from "https://en.wikipedia.org/w/index.php?title=James_Remar&oldid=832055566"
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Harvest for the World
From Wikipedia, the free encyclopedia
Jump to: navigation, search
For the song, see Harvest for the World (song).
Harvest For The World
Studio album by The Isley Brothers
Released
May 1976[1]
Recorded
1975–1976
Studio
The Record Plant
(Los Angeles, California)
Genre
Soul, funk rock, smooth soul
Length
37:54
Label
T-Neck Records
Producer
The Isley Brothers
The Isley Brothers chronology
The Heat Is On
(1975)The Heat Is On1975 Harvest for the World
(1976) Go for Your Guns
(1977)Go for Your Guns1977
Harvest for the World is the fourteenth album released by The Isley Brothers on their T-Neck imprint in May 1976.
The album was remastered and expanded for inclusion in the 2015 released CD box set The RCA Victor & T-Neck Album Masters, 1959–1983.
Contents
[hide]
1 Reception
2 Track listing
3 Personnel
4 Later samples and covers
5 Charts
5.1 Singles
6 See also
7 External links
8 References
Reception[edit]
Professional ratings
Review scores
Source
Rating
Allmusic [2]
Robert Christgau B- [3]
Pitchfork 9.0/10[4]
The album included the successful socially conscious title track and the top three R&B record, "Who Loves You Better?" While not released as singles, the ballads "(At Your Best) You Are Love" and "Let Me Down Easy" were also hits. The album sold over 500,000 copies in the first three weeks of release, making it one of the fastest-selling records ever (it passed the million sales mark in the early 2000s). It topped the Billboard R&B Albums chart; the Isleys third straight album to do so.
Track listing[edit]
Unless otherwise noted, Information is based on Liner notes[5]
All tracks written by Ernie Isley, Marvin Isley, Chris Jasper, Rudolph Isley, O'Kelly Isley and Ronald Isley.
Side one
No.
Title
Length
1. "Harvest for the World (Prelude)" 2:11
2. "Harvest for the World" 3:51
3. "People of Today" 4:42
4. "Who Loves You Better" 5:31
Side two
No.
Title
Length
5. "(At Your Best) You Are Love" 5:23
6. "Let Me Down Easy" 6:30
7. "So You Wanna Stay Down" 3:51
8. "You Still Feel the Need" 4:50
[show]2001 reissue bonus track
No.
Title
Writer(s)
Length
9. "Summer Breeze" (Live at Bearsville Studios) Jim Seals, Dash Crofts 8:43
Personnel[edit]
Performance
Ronald Isley – lead vocals (1-7)[6]
O'Kelly Isley, Jr. – lead vocals (6)[1], background vocals
Rudolph Isley – lead vocals (8)[7], background vocals
Ernie Isley – congas, other percussion (2, 5)[8][9], timbales, maracas[1], electric guitar, six-string acoustic guitar, 12-string acoustic guitar, drums
Marvin Isley – bass, cowbell, percussion
Chris Jasper – tambourine, other percussion (2, 5)[8][9], acoustic piano, electric piano, ARP synthesizer, clavinet
Production
The Isley Brothers - producers
Malcolm Cecil - recording engineer (1-8), producer, music programming
John Holbrook - live recording engineer (9)
Later samples and covers[edit]
Later Samples
Paul Johnson sampled "Harvest for the World" for his song “4 the World”, from the 1995 album Bump Talkin’[10]
Mo Kolours also sampled "Harvest for the World" for his song “Harvest”, which first appeared on the 2015 album Texture Like Sun[11]
Tracey Lee sampled "Let Me Down Easy" on his song “On the Edge”, from the 1997 album Many Facez
Devin the Dude also reused "Let Me Down Easy" on the song “I Can’t Handle It”, from his 2010 album Suite 420
Cover Versions
Power Station covered "Harvest for the World" on their album The Power Station in 1985.
Ronnie Laws first recorded the song "Harvest for the World" with the Isley Brothers themselves for his 1992 album Deep Soul[12], then later covered the entire album of "Harvest for the World" titled Portrait of the Isley Brothers' Harvest for the World in 1998.[13]
Aaliyah covered "(At Your Best) You Are Love" on her album Age Ain't Nothing but a Number in 1994.
Jewell covered "Harvest for the World" on the soundtrack album Murder Was the Case in 1994.
Mike Francis covered "Harvest for the World" in both English and Italian. The Italian version, known as "Il Mio Amore Libero per Te", first appeared on his 1998 album Misteria.[14][15]
Vanessa Williams covered "Harvest for the World" on her album Everlasting Love in 2005.
Frank Ocean covered “At Your Best (You Are Love)” in early 2015[16], later appearing on his 2016 video album Endless.
The Christians famously covered "Harvest for the World" in 1988. The song reached #8 in the UK Singles chart[17]
Charts[edit]
Chart (1976)
Peak
position
Billboard Pop Albums[18] 9
Billboard Top Soul Albums[18] 1
Singles[edit]
Year
Single
Chart positions[19]
US
Pop
US
R&B
US
Dance
1976 "Who Loves You Better" 47 3 2
"Harvest for the World" 63 9 –
"People of Today" – – 3
See also[edit]
List of number-one R&B albums of 1976 (U.S.)
External links[edit]
The Isley Brothers-Harvest For The World at Discogs
References[edit]
^ Jump up to: a b c ”Albums Recorded by The Isley Brothers”. The Isley Brothers. http://www.softshoe-slim.com/lists/i/isley.html#16
Jump up ^ Lytle, Craig. The Isley Brothers: Harvest For The World > Review at AllMusic. Retrieved 03 September 2011.
Jump up ^ "Robert Christgau review". Robertchristgau.com. Retrieved 2013-04-21.
Jump up ^ Erlewine, Stephen Thomas (September 11, 2015). "The Isley Brothers: The RCA Victor and T-Neck Album Masters". Pitchfork. Retrieved December 23, 2015.
Jump up ^ The Isley Brothers. “Harvest for the World” (Album notes). T-Neck / Epic. 1976.
Jump up ^ Bogdanov, Vladimir. “All Music Guide to Soul...”. Hal Leonard Corporation. 2003. https://books.google.com/books?id=o552g5xRRiwC&pg=PA342&lpg=PA342&dq=isley+brothers+let+me+down+easy+lead+vocals+by+o’kelly&source=bl&ots=z8f1mZsotg&sig=Chdtqz83KvxcZ1tItqiwI6dfAmA&hl=en&sa=X&ved=0ahUKEwje_vCmhp_YAhWiY98KHRSoAbsQ6AEIiAEwEg#v=onepage&q=isley%20brothers%20let%20me%20down%20easy%20lead%20vocals%20by%20o’kelly&f=false
Jump up ^ Disco, Soul, Gold. “Happy Birthday, Rudolph Isley”. Facebook. 2 April 2015. https://m.facebook.com/DiscoSoulGold/posts/998121983534342
^ Jump up to: a b ”Harvest for the World”. YouTube: The Isley Brothers - Topic. 9 February 2017. https://m.youtube.com/watch?v=Y0OOvVN8TcA
^ Jump up to: a b ”(At Your Best) You Are Love”. YouTube: The Isley Brothers - Topic. 17 February 2017. https://m.youtube.com/watch?v=CSGMkGHty6o
Jump up ^ Johnson, Paul. “Bump Talkin’” (Album notes). Peacefrog Records. 1995.
Jump up ^ McDermott, Matt. “Mo Kolours announces Texture Like Sun LP”. Resident Advisor. 15 September 2015. https://www.residentadvisor.net/news.aspx?id=31342
Jump up ^ Laws, Ronnie. “Deep Soul”. Par Records. 1992. https://www.allmusic.com/album/deep-soul-mw0000096056
Jump up ^ Laws, Ronnie. “Portrait of The Isley Brothers’ Harvest...”. Blue Note. 24 March 1998. https://www.allmusic.com/album/portrait-of-the-isley-brothers-harvest-for-the-world-mw0000597443
Jump up ^ “It’s a Sony”. Mike Francis Archives. Updated 7 March 2001. http://wohnort.org/francis/archive.html
Jump up ^ Francis, Mark. “Misteria”. Spotify / Lungomare S.r.l. 1998. https://open.spotify.com/album/0qyH2J7H3rnLEP0cEhwB7Z
Jump up ^ Kreps, Daniel. “Frank Ocean Shares Soulful Aaliyah Tribute...”. Rolling Stone. 17 January 2015. https://www.rollingstone.com/music/news/frank-ocean-shares-soulful-aaliyah-tribute-at-your-best-you-are-love-20150117
Jump up ^ The Christians. “Harvest...FLAC”. YouTube: A-Music. 26 November 2016. https://m.youtube.com/watch?v=KYuN1sz3TFQ
^ Jump up to: a b "The Isley Brothers US albums chart history". allmusic.com. Retrieved 2011-09-03.
Jump up ^ "The Isley Brothers US singles chart history". allmusic.com. Retrieved 2011-09-03.
[show]
v
t
e
The Isley Brothers
Ernie Isley
Marvin Isley
O'Kelly Isley, Jr.
Ronald Isley
Rudolph Isley
Chris Jasper
Studio albums
Shout!
Twist & Shout
Twisting and Shouting
This Old Heart of Mine
Soul on the Rocks
It's Our Thing
The Brothers: Isley
Get into Something
Givin' It Back
Brother, Brother, Brother
3 + 3
Live It Up
The Heat Is On
Harvest for the World
Go for Your Guns
Showdown
Winner Takes All
Go All the Way
Grand Slam
Inside You
The Real Deal
Between the Sheets
Masterpiece
Smooth Sailin'
Spend the Night
Tracks of Life
Mission to Please
Eternal
Body Kiss
Baby Makin' Music
Live albums
Live at Yankee Stadium
The Isleys Live
Live!
Compilation albums
Timeless
Singles
"I'm Gonna Knock on Your Door"
"Shout (Part 1)"
"How Deep Is the Ocean?"
"Twist and Shout"
"Nobody but Me"
"Testify (Part 1)"
"Love Is a Wonderful Thing"
"This Old Heart of Mine (Is Weak for You)"
"I Guess I'll Always Love You"
"That's the Way Love Is"
"Take Me in Your Arms (Rock Me a Little While)"
"Behind a Painted Smile"
"Put Yourself in My Place"
"It's Your Thing"
"I Turned You On"
"Keep On Doin'"
"Freedom"
"Love the One You're With"
"Spill the Wine"
"Lay Lady Lay"
"Lay-Away"
"Pop That Thang"
"Work to Do"
"It's Too Late"
"That Lady (Part 1)"
"What It Comes Down To"
"Summer Breeze"
"Live It Up"
"Fight the Power (Part 1)"
"For the Love of You"
"Harvest for the World"
"The Pride"
"Livin' in the Life"
"Voyage to Atlantis"
"Take Me to the Next Phase (Part 1)"
"Groove with You"
"I Wanna Be with You (Part 1)"
"It's a Disco Night (Rock Don't Stop)"
"Don't Say Goodnight (It's Time for Love) (Parts 1 & 2)"
"Between the Sheets"
"Choosey Lover"
"Down Low (Nobody Has to Know)"
"Contagious"
See also
Discography
T-Neck Records
Isley-Jasper-Isley
Book:The Isley Brothers
Category:The Isley Brothers
Portal:R&B and Soul Music
Retrieved from "https://en.wikipedia.org/w/index.php?title=Harvest_for_the_World&oldid=816944606"
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Visit the main page

values:
/wiki/Main_Page
Visit the main page [ctrl-alt-z]
z

values: Featured content – the best of Wikipedia

values: Find background information on current events

values:
/wiki/Special:Random
Load a random article [ctrl-alt-x]
x

values: portal navigation p-navigation p-navigation-label

values: Guidance on how to use and edit Wikipedia

values: About the project, what you can do, where to find things

values: A list of recent changes in the wiki [ctrl-alt-r]

values: portal navigation p-interaction p-interaction-label

values: List of all English Wikipedia pages containing links to this page [ctrl-alt-j]

values: Recent changes in pages linked from this page [ctrl-alt-k]

values:
/wiki/Wikipedia:File_Upload_Wizard
Upload files [ctrl-alt-u]
u

values: A list of all special pages [ctrl-alt-q]

values: Permanent link to this revision of the page

values: Link to connected data repository item [ctrl-alt-g]

values: Printable version of this page [ctrl-alt-p]

values:
uls-settings-trigger
Language settings
0
button
true

values: /static/images/wikimedia-button-1.5x.png 1.5x, /static/images/wikimedia-button-2x.png 2x

values: /static/images/poweredby_mediawiki_132x47.png 1.5x, /static/images/poweredby_mediawiki_176x62.png 2x

values:
suggestions
display: none; font-size: 13px;

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