Abstract: We reconsider several studies of species arrangements over a set of islands or quadrats; for all but one, absence of certain species combinations was taken to indicate competitive exclusions. In every instance mathematical error or lack of a properly framed null hypothesis casts these claims into doubt. An alternative hypothesis, that species colonize sites independently of the presence of other species, but at different rates or with different probabilities of survival, was tested by computer simulation and found to be consistent with most of the data. Even when it is inconsistent, one cannot from the arrangement alone conclude that species interactions are occurring.

Abstract: The form of the Johnson-Neyman region of significance is shown to be determined by the statistic for testing the null hypothesis that the population within-group regressions are parallel. Results are obtained for both simultaneous and nonsimultaneous regions of significance.

Abstract: A comparative study is made of three tests, developed by James (1951), Welch (1951) and Brown & Forsythe (1974). James presented two methods of which only one is considered in this paper. It is shown that this method gives better control over the size than the other two tests. None of these methods is uniformly more powerful than the other two. In some cases the tests of James and Welch reject a false null hypothesis more often than the test of Brown & Forsythe, but there are also situations in which it is the other way around. We conclude that for implementation in a statistical software package the very complicated test of James is the most attractive. A practical disadvantage of this method can be overcome by a minor modification.

Abstract: It has become popular in recent years to assess the economic consequences of new financial reporting standards and disclosure requirements as reflected in stock price behavior. While the motivation for such studies seems to be generally accepted, there are serious problems both in designing studies to assess the capital market reaction to new accounting rules, and in subsequently interpreting the results for policymaking. The difficulties are largely due to the lack of tight models of how new Financial Accounting Standards Board (FASB) standards and Securities and Exchange Commission (SEC) releases should impact investor decisions within the context of efficient markets. This generally leads the researchers to test for average abnormal stock returns upon the announcement of a new accounting rule across a sample of firms subject to the rule. This empirical approach is exposed to two major dangers. First, the intrusion of confounding events can easily lead to rejection of the null hypothesis of no price response due to both the very general nature of the alternate hypothesis of average abnormal returns and the single event date.'

Abstract: An Edgeworth expansion with remainder o(N- 1) is established for simple linear rank statistics under the null-hypothesis. The theorem is proved for a wide class of scores generating functions which includes the normal quan tile function.

Abstract: The prices of opening transactions on the New York Stock Exchange are determined quite differently from prices of subsequent transactions. This paper tests the null hypothesis that opening prices are as representative of contemporaneous equilibrium stock values as subsequent intra-day transactions prices. With one possible exception, there is no basis for rejecting this hypothesis, despite the very different trading mechanisms used in opening trades and intra-day trades.

Abstract: As Reed and Slaichert point out in an article in this issue (see p 1307), two types of errors may be made when an experiment is designed and carried out that involves the testing of a hypothesis. One may erroneously reject a true hypothesis, or one may equally erroneously accept a false one. In most studies using this design, the type I error (the rejection of a true hypothesis) is usually discussed and limited to a risk of 5% or 1%. Few researchers in the medical field ever look at or discuss the probability of making a type II error (the acceptance of a false hypothesis). For example, if one is testing the hypothesis that drugAis equal to drugB, in most cases, the researcher would simply perform an experiment, and if the difference observed between the two drugs was "statistically significant" at some preassigned level of risk,

Abstract: The subjects for this study were tested using MMPI Scales 2 and 4 and the Beck Depression Inventory There were four different groups studied, adolescent male patients, adolescent female patients, mothers, and fathers The first null hypothesis stated that there will be no significant incidence of depression among adolescents hospitalized in a specific hospital facility It is obvious that the null hypothesis was rejected for adolescents, both male and female, in the sample on the basis of the MMPI results The second null hypothesis stated that there will be no significant incidence of depression among parents of adolescents admitted to a specific hospital for psychiatric treatment There is not sufficient evidence to suggest that parents are depressed to a significant degree; therefore, the second null hypothesis is not rejected based on the results of the tests used in this study However, there were a significant number of fathers who fell within the range of mild depression Mothers did not appear depressed The third null hypothesis stated that there will be no significant relationship between the presence of depression in hospitalized adolescents and the presence of depression in one or both parents There was not evidence to permit rejection of this hypothesis; thus, there is not proof on the basis of this study that there is a correlation between family members

Abstract: It is often interesting to compare the size of treatment effects in analysis of variance designs. Many researchers, however, draw the conclusion that one independent variable has more impact than another without testing the null hypothesis that their impact is equal. Most often, investigators compute the proportion of variance each factor accounts for and infer population characteristics from these values. Because such analyses are based on descriptive rather than inferential statistics, they never justify the conclusion that one factor has more impact than the other. This paper presents a novel technique for testing the relative magnitude of effects. It is recommended that researchers interested in comparing effect sizes apply this technique rather than basing their conclusions solely on descriptive statistics.

Abstract: Many nurse investigators, although trained in research methodology and statistics, have difficulty deciding which statistical test of significance to use for a particular research hypothesis or question. This paper presents a decision tree approach to guide investigators in selecting an appropriate statistical test for several different research situations. The decision tree is a series of questions; the answers lead the user to a decision about which statistical test to use. It is recommended for investigators who have basic training in research methodology and statistics; details on how to carry out any of the statistical tests contained herein can be found in most introductory statistics textbooks.

Abstract: Given the usual normal multivariate linear regression model Y = BX + E, with B subjected to double linear restrictions GBF' = T, a likelihood ratio test criterion for testing the composite linear null hypothesis HBJ' = U; G, F, T, H, J, U specified, is provided. The applications of such tests are discussed by Timm (1980).

Abstract: The problem i n v e s t i g a t e d i n t h i s s tu d y in v o lv e d a com parison o f t h e s e l f e v a l u a t i o n o f te a c h in g s k i l l s as p e r c e iv e d by s tu d e n t t e a c h e r s and th e e v a lu a t io n o f t h e s e s k i l l s by t h e i r c o r r e s p o n d in g s u p e r v i s in g t e a c h e r s . The s p e c i f i c q u e s t io n s to be answ ered w ere : 1. Can s tu d e n t t e a c h e r s e f f e c t i v e l y p r e d i c t and a s s e s s t h e i r t e a c h in g s t r e n g t h s and w eaknesses? 2. Does an i n s t r u c t i o n a l sequence combined w i th th e s e l f e v a l u a t i o n o f v id e o ta p e d te a c h in g p e rfo rm an ce a id in im prov ing s tu d e n t t e a c h e r e f f e c t i v e n e s s i n th e s e l f e v a l u a t i o n o f te a c h in g co m p e ten c ie s? The sam ple f o r P a r t One o f th e s tu d y c o n s i s t e d o f 131 s tu d e n t s e n r o l l e d i n s t u d e n t t e a c h in g a t L o u is ia n a S t a t e U n iv e r s i t y , B aton Rouge, L o u is ia n a , d u r in g th e s p r in g s e ­ m e s te r o f 1980. T h e i r r e s p e c t i v e s u p e r v i s in g t e a c h e r s w ere a l s o in v o lv e d . The s tu d e n t t e a c h e r s p ro v id e d s e l f e v a l u a ­ t i v e d a t a th ro u g h t h e i r c o m p le t io n o f th e In s t ru m e n t f o r t h e S e lf -R a n k in g o f T each in g S k i l l s (ISRTS) p r i o r t o th e b e g in n in g o f th e s p r in g s e m e s te r and th e D ia g n o s t ic I n s t r u ­ m ent f o r S tu d e n t T each in g P erfo rm an c e (DISTP) d u r in g th e f i f t h week o f th e s e m e s te r . The s u p e r v i s i n g t e a c h e r s p ro v id e d e v a l u a t i v e d a t a c o n c e rn in g th e t e a c h in g p e r ­ form ance o f t h e i r r e s p e c t i v e s t u d e n t t e a c h e r s th ro u g h vii t h e i r co m p le t io n o f t h e DISTP d u r in g th e f i f t h week. These d a t a were a n a ly z e d th ro u g h th e u se o f Spearman ran k c o r r e l a t i o n c o e f f i c i e n t s and c h i s q u a r e t e s t s . Four n u l l h y p o th e s e s were t e s t e d f o r s i g n i f i c a n c e a t th e .05 l e v e l . P a r t Two o f t h e s tu d y in v o lv e d 56 s tu d e n t t e a c h e r s and t h e i r r e s p e c t i v e s u p e r v i s in g t e a c h e r s . Of t h i s num­ b e r , th e 28 s tu d e n t t e a c h e r s a s s ig n e d to th e L o u is ia n a S t a t e U n iv e r s i t y L a b o ra to ry School a lo n g w i th t h e i r s u p e r ­ v i s i n g t e a c h e r s com prised t h e e x p e r im e n ta l g roup . The c o n t r o l group c o n s i s t e d o f 28 s tu d e n t t e a c h e r s a s s ig n e d to o ff-cam p u s s tu d e n t t e a c h in g l o c a t i o n s and t h e i r r e ­ s p e c t i v e s u p e r v i s in g t e a c h e r s . The s tu d e n t t e a c h e r s and s u p e r v i s in g t e a c h e r s i n b o th g ro u p s com pleted th e DISTP d u r in g th e f i f t h w e e k o f th e s e m e s te r . The e x p e r im e n ta l group o f s t u d e n t t e a c h e r s th e n r e c e iv e d i n s t r u c t i o n in th e u s e o f th e S e l f E v a l u a t i o n In s t ru m e n t to be u sed in c o n ju n c t io n w i th t h e v ie w in g o f t h e i r own v id e o ta p e d te a c h in g p e r fo rm a n c e . Each o f th e 28 e x p e r im e n ta l -g ro u p s tu d e n t t e a c h e r s was v id e o ta p e d d u r in g t h r e e s e p a r a t e 15 m in u te te a c h in g segm ents a t e i g h t to t e n day i n t e r v a l s . Each s tu d e n t t e a c h e r v iew ed h i s t e a c h in g segm ent and e v a lu a te d h i s p e rfo rm a n ce by co m p le t in g th e S e l f -E v a lu a t io n In s t r u m e n t on each o c c a s io n . The c o n t r o l g r o u p s tu d e n t t e a c h e r s w ere n o t v id e o ta p e d and d id n o t com ple te th e S e l f E v a lu a t io n I n s t r u m e n t . At t h e end o f t h e s e m e s te r , b o th g roups o f s tu d e n t t e a c h e r s and s u p e r v i s in g t e a c h e r s a g a in viii com pleted t h e DISTP. T hree a n a l y s i s o f v a r i a n c e p r o ­ c e d u re s w ere u se d t o a n a ly z e th e d a t a . Nine n u l l h y p o th e ­ s e s were t e s t e d f o r s i g n i f i c a n c e a t th e .05 l e v e l . I n t e r p r e t a t i o n s o f th e d a t a c o l l e c t e d w i th in t h i s s tu d y le d to t h e f o l lo w in g c o n c lu s io n s : 1 . The s t u d e n t t e a c h e r s in v o lv e d i n t h i s s tu d y w ere u n a b le t o p r e d i c t and a s s e s s t h e i r te a c h in g s t r e n g t h s and w eak n esses . 2. An i n s t r u c t i o n a l sequence combined w i th th e s e l f e v a l u a t i o n o f t h e i r own v id e o ta p e d te a c h in g p e r ­ form ance was n o t v a l u a b l e in im prov ing s tu d e n t t e a c h e r e f f e c t i v e n e s s i n t h e s e l f e v a l u a t i o n o f te a c h in g compe­ t e n c i e s when c o r re s p o n d in g s u p e r v i s in g t e a c h e r r a t i n g s w ere used as t h e s t a n d a r d . 3. S tu d e n t t e a c h e r s p e r c e iv e d t h e i r t e a c h in g com petenc ies to im prove d u r in g th e s tu d e n t te a c h in g ex ­ p e r i e n c e . 4 . D i f f e r e n c e s i n s u p e r v i s in g te a c h e r p e r ­ c e p t io n s o f e f f e c t i v e te a c h in g made a consensus r e g a r d in g th e d eg ree o f change e x p e r ie n c e d by s tu d e n t t e a c h e r s d i f f i c u l t to a c h ie v e .

Abstract: Strong correlations have been observed between potential indices and the densities of spatial variables. The conventional null hypothesis of bivariate regression is inappropriate for testing their significance. A randomization test is proposed and is applied to 1975 US population data by state. The resulting relationship has a significant correlation, but its slope could occur frequently under the null hypothesis. The correlation is shown to be related to the spatial autocorrelation of densities by constructing arrangements with prescribed values of the modified Moran index.

Abstract: The previous chapters dealt with inference procedures applicable in one-sample (or paired-sample) problems. We now consider the situation where there are two mutually independent random samples, one from each of two populations. We discuss tests which apply to the null hypothesis that the two populations are identical and the confidence procedures related to these tests.

Abstract: To date, the results of studies which attempted to estimate residential water demand models have varied, but the source of these variations is not evident because the studies have applied different methodologies and data bases to different regions. The purpose of this paper is to develop models of residential water demand for watershed regions and test the null hypothesis that a single model is adequate to explain variations for all of the individual regions. Primary data collected from questionnaires and utility company records is used in a regression analysis to estimate a generalized water demand model for the state as well as one for each of the subregions. The null hypothesis is rejected which indicates that there are other factors which influence the demand for water and the use of a single model could result in biased estimates.

Abstract: The intent of the study was to investigate the morale of teachers in a selected south Louisiana secondary school. Four null hypotheses were proposed and tested to identify the effect of a change of facility upon the entire group of teachers; male and female teachers; teachers under the age of thirty-seven and those who were thirty-seven years of age or older; and teachers having bachelors de­ grees and teachers with higher degrees that moved to a new school plant. All forty-three teachers (N=43) employed at a selected secondary school participated in the experiment. Of that total, nineteen teachers moved to a new facility and twenty-four remained at the existing facility. There were no changes in teacher assignments, classloads, or teaching materials as a result of the change in school plants. The Purdue Teacher Opinionaire, a one hundred item instrument, was administered to each group in the fall of 1977 and the spring of 1978. The experimental group moved to the new facility in February of 1978. An analysis of covariance was computed for each of the four null hypotheses. Each hypotheses was tested at the .05 level of significance.

Abstract: A method is presented for testing whether a pair of pre-treatment by post-treatment data matrices from a drug vs. placebo study can be partitioned into drug-typical and placebo-typical regions. A large sample Chi square test is derived for testing a specific partition posited a priori and a generalized Chi square test over a set of searched partitions is also derived. Some Monte Carlo tests are reported for the generalized test which confirm that the upper tails of the Chi square distribution provide appropriate probability levels for testing the null hypothesis that both samples are drawn from the same population. When the samples are drawn from different populations whose differences are well described by traditional parametric models, ANOCOVA or a test for differences in slope were more powerful in rejecting the null hypothesis. When two populations were chosen whose difference was not well described by these models, the newly derived test was more powerful.

Abstract: Previous studies have indicated that fertility tends to be inversely related to level of education. Thus the author hypothesized that there would be no difference between the undergraduates of a Nigerian university and those at an American university with regards to opinions on family size. This null hypothesis was found to be untrue; Nigerian students, both male and female, preferred large families when compared to their U.S. counterparts.

Abstract: ............................................ v i i i C h a p te r 1 . INTRODUCTION ................................................................'............... 1 B ackground o f th e P r o b l e m ........................................ 1 S ta te m e n t o f th e P rob lem ..................... 1 H y p o th e se s ................................................................................ 4 B a s ic A ssu m p tio n s ....................................................... 4 Im p o rta n c e o f th e S t u d y ................................................ 6 D e f i n i t i o n o f Term s .......................................................... 8 D e l im i ta t i o n s o f th e S tu d y .......................... 10 O r g a n iz a t io n o f th e S tu d y ............................................ 11 2 . REVIEW OF RELATED LITERATURE ..................................................14 Summary ............................................................................ 20 3 . DESCRIPTION OF THE STUDY ................................................... 23 G e n e ra l D esig n ................... 23 P o p u la t io n ............................................................................. 26 D a ta and I n s t r u m e n ta t io n .............................................. 28 A n a ly s is o f D a ta ................................................................. 29 C h a p te r P age 4 . PRESENTATION AND ANALYSIS OP DATA .......................... 30 I n t r o d u c t i o n ............ 30 T re a tm e n t o f D a ta ............................................................... 31 T e s t in g H y p o th e se s ........................................................ 32 T re a tm e n t o f D a ta f o r F i r s t G rade ..................... 50 R e a d in g a c h ie v e m e n t .................................... 51 M a th e m a tic s a c h ie v e m e n t ............................ 52 Sex-C om pared a c h ie v e m e n t .................... ’............... 52 R e la t io n s h ip B etw een F i r s t G rade A n a ly s is an d T h a t o f O th e r G rad es 53 5 . SUMMARY. CONCLUSIONS, AND RECOMMENDATIONS .............. 60 S u m m a ry ................ 60 C o n c lu s io n s ............................................................................. 62 R ecom m endations ............ 67 BIBLIOGRAPHY ................................................................................................... 68 APPENDICES ........................................................................................................ 74 A. LETTER OF PERMISSION .............................................................. 74 B. DATA COLLECTION FORM ...................................... i 75 C. DATA TABULATION FORM .............................................................. 76 D. DATA ANALYSIS FORM ................................................................... 77 VITA ....................................................................................................................... 79

Abstract: The international comparison of organisations in near‐identical situations with regard to size, technology, the task environment, dependence and location suggests itself as the most appropriate opportunity to test the “null hypothesis” of the cultural influence on organisation structures for the purposes of this study. The overall design of the project is based on earlier French research work, which had initiated cross‐national comparisons in the early 1970s. This article specifically focuses on British‐German comparisons.

Abstract: : This report considers a class of hypothesis tests in which the (null) hypothesis is rejected only after being rejected on the basis of each of two samples. The motivation for these procedures is that their average sample sizes under the null hypothesis will be very near that of a fixed-sample-size test using only the first sample, while their error-probability performance should be superior. The validity of these properties is verified numerically for the particular problem of location testing with normal errors by considering the power functions and average sample sizes of linear versions of these tests. Also, the Pitman asymptotic efficiencies of the proposed test are compared to those of fixed-sample-size tests and sequential probability ratio tests, indicating that the proposed tests are intermediate to these two alternatives. However, the complexity and other properties of the proposed tests are comparable to those of the fixed-sample-size test, making their use desirable for many applications.

Abstract: In the theory and practice of statistical inference, multiple decision problems are encountered in many experimental situations. The classical methods for analyzing data do customarily employ hypothesis testing in most situations. In such cases, when the hypothesis is rejected, one wants to know in which of a number of possible ways the actual situation (true state of nature) differs from the one postulated by the null hypothesis. If, in the formulation of the problem, we consider only two decisions (reject or not reject the hypothesis), we will not only neglect to differentiate between certain alternative decisions but may also be using an inappropriate acceptance region for the hypothesis. Moreover, the traditional approach to hypotheses testing problems is not formulated in a way to answer the experimenter’s question, namely, how to identify the “best” (in some sense) population? For example, the method of the least significant differences based on the t-test has been used in the past to detect differences between the true unknown means of different varieties and thereby choosing the population which is the “best”, say, the one with the largest mean. But this method is indirect, less efficient and does not provide an overall probability of a correct decision. The remark (criticism) is also valid, to some extent, for methods based on multiple comparison techniques. The traditional approach does not allow for a decision if the null hypothesis is not rejected.

Abstract: For diseases of unknown or uncertain aetiology, it is often of interest to test epidemiologically hypotheses concerning the possible existence of an infectious agent. Notably such studies concern Burkitt’s Lymphoma (1), childhood leukaemia (2) and multiple sclerosis (3). Since Knox (4) originally formalised the concept of space-time interaction and formulated a statistical test for its existence, a number of other tests have been proposed and applied to various diseases and conditions. When contemplating an infectious agent, it is clearly of importance to consider case-to-case contact and hence to consider the incubation, or latent, period of the disease. Although most of these statistical tests are not conceptually adequate for use with diseases other than those with very short incubation periods — they only consider one place and one time for each patient — Pike and Smith (5) consider a susceptible-infective model which does appear to be logically applicable to such situations in that it allows the natural history of the disease to be specified in terms of a period of susceptibility (during which the patient would have contracted the disease) and a period of infectivity (during which the patient would have been able to infect other potential patients). The statistical test formulated by Pike and Smith considers, for all possible pairs of patients who are infective and/or susceptible within the area under study during the study period, whether or not one patient was in the right place at the right time to infect the other patient. The test statistic is the number of such concordant pairs. Under the null hypothesis of no space-time interaction, the approximate distribution of the test statistic is available for testing this null hypothesis against the hypothesis of space-time clustering of the form specified in the hypothesised natural history of the disease.

Abstract: Procedure. The procedure used to compare these two policies was the same each semester and tables were used to make the data useful. All the tardies for the first semester were recorded by student, by the class the student was in, and by the total school population. The tardies for the second semester were gathered the same way. All this informa­ tion was then placed in tables for comparisons. The use of parent communication was also explained in the report. Each class was compared within each policy and then compared to each other after the results were tabUlated. A "t" test was administered to test the null hypothesis: The Mean of Policy A is equal to the Mean of Policy B. Conclusion. The null hypothesis was rejected since

Abstract: The foundations of statistics are controversial, as foundations usually are. The main controversy is between so-called Bayesian methods, or rather neo-Bayesian, on the one hand and the non-Bayesian, or ‘orthodox’, or sampling-theory methods on the other.1 The most essential distinction between these two methods is that the use of Bayesian methods is based on the assumption that you should try to make your subjective or personal probabilities more objective, whereas anti-Bayesians act as if they wished to sweep their subjective probabilities under the carpet. (See, for example, Good (1976).) Most anti-Bayesians will agree, if asked, that they use judgment when they apply statistical methods, and that these judgments must make use of intensities of conviction,2 but that they would prefer not to introduce numerical intensities of conviction into their formal and documented reports. They regard it as politically desirable to give their reports an air of objectivity and they therefore usually suppress some of the background judgments in each of their applications of statistical methods, where these judgments would be regarded as of potential importance by the Bayesian. Nevertheless, the anti-Bayesian will often be saved by his own common sense, if he has any. To clarify what I have just asserted, I shall give some examples in the present article.