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Table 10. Summary of Hypothesis Testing Hypothesis Effect

in IS BIGGER ALWAYS BETTER? TOWARD A RESOURCE-BASED MODEL OF OPEN SOURCE SOFTWARE DEVELOPMENT COMMUNITIES. By
by Glen Sagers 2007
"... In PAGE 6: ...able 9. Factor Loadings and Cross-Loadings for Multi-Item Scales...........................................60 Table10 .... In PAGE 72: ... Similarly, there are indications that a more successful software product and a more successful project community can subsequently increase the size of the community. Table10 presents a summary of hypothesis support.... ..."

Table 1. Results of Hypothesis Tests Hypothesis t-

in Running Up the Bid: Modeling Seller Opportunism in Internet Auctions
by Robert J. Kauffman, Charles A. Wood

Table 18. Hypothesis and test statistics for signiflcance testing Hypothesis Test statistic

in A JOINT TASK FORCE COMMANDER
by Old Dominion University, Mikel D. Petty (director, R. Bowen Loftin (member, Frederic D. Mckenzie (member, Gary E. Luck (member, Joseph Psotka (member, John Anthony Sokolowski, John Anthony Sokolowski, Director Dr, Mikel D. Petty 2003
"... In PAGE 97: ... Figure 14 de- picts the two one-sided hypothesis tests. Table18 lists the hypotheses for each test and its associated test statistic. X represents the sample mean.... ..."

Table 3: Summary of hypothesis testing

in Improving Speech Playback using Time-Compression and Speech Recognition
by Sunil Vemuri, Philip DeCamp, Walter Bender, Chris Schmandt 2004
"... In PAGE 7: ...Table 3: Summary of hypothesis testing Table3 summarizes hypothesis testing for both the Phase 1 subjective tests and Phase 2 question-answering tests. DISCUSSION The perfect transcript style (C1) is tantamount to reading and, not-surprisingly, results from both Phase 1 (self-reported maximum) and Phase 2 (question-answering task) suggest this style is the best supplement to improving comprehension of speech playback.... ..."
Cited by 10

Table 3: Summary of hypothesis testing

in Improving Speech Playback using Time-Compression and Speech Recognition
by Sunil Vemuri, Philip Decamp, Walter Bender, Chris Schmandt 2004
"... In PAGE 7: ...Table 3: Summary of hypothesis testing Table3 summarizes hypothesis testing for both the Phase 1 subjective tests and Phase 2 question-answering tests. DISCUSSION The perfect transcript style (C1) is tantamount to reading and, not-surprisingly, results from both Phase 1 (self- reported maximum) and Phase 2 (question-answering task) suggest this style is the best supplement to improving comprehension of speech playback.... ..."
Cited by 10

Table 2: Hypothesis test for means

in GROSS ERRORS DETECTION OF INDUSTRIAL DATA BY NEURAL NETWORK AND CLUSTER TECHNIQUES
by R. M. B. Alves, C. A. O. Nascimento 2002
"... In PAGE 3: ... For this step, the hypothesis test for means, which involves a confidence interval estimate and a hypothesis test was employed with a confidence level of 95% (Himmelblau, 1970). Table2 shows the application of this methodology in analysis of plant data. The values in bold in groups 1 and 2 were not well adjusted during neural network training and it was not possible to identify groups of similar data sets for the cluster analysis; thus a hypothesis test for means analysis was performed.... ..."

Table 6: Results of hypothesis tests

in Fault detection capabilities of coupling-based oo testing
by Roger T. Alexander 2002
"... In PAGE 9: ....3. Hypothesis tests Log-linear analysis permits one to analyze categorical data in much the same manner as in analysis of variance. The sampling distribution underlying Table6 is a product of independent multinomials. According to Bishop, Fienberg and Holland, the kernel of the appropriate likelihood function is the same as that for a simple multinomial or a simple Poisson [7].... In PAGE 10: ... Thus, we do not reject the null hypothesis (H0), and hence conclude that there is no interaction between these two factors. For the remaining hypothesis tests, we selected out only the data for a particular pair of criteria (indicated by the column labeled Hypothesis in Table6 ) and then tested for an interaction between these two by fitting the model described with and without the corresponding fault-type/criterion term. Table 6 summarizes the results of these tests.... In PAGE 10: ... For the remaining hypothesis tests, we selected out only the data for a particular pair of criteria (indicated by the column labeled Hypothesis in Table 6) and then tested for an interaction between these two by fitting the model described with and without the corresponding fault-type/criterion term. Table6 summarizes the results of these tests. The column labeled Hypothesis states the null (H0) and alternative hypothesis (H1) for each test.... In PAGE 10: ... 6. Discussion The three hypotheses in Table6 that tested the effectiveness of each coupling-based criteria against Branch Coverage indicate that the coupling criteria are better at detecting the object-oriented faults used in the experiment. A remaining question is which of the three coupling criteria is the most effective.... ..."
Cited by 3

Table 6: Results of hypothesis tests

in Fault Detection Capabilities of Coupling-based OO Testing
by Roger T. Alexander, Jeff Offutt, James M. Bieman 2002
"... In PAGE 9: ....3. Hypothesis tests Log-linear analysis permits one to analyze categorical data in much the same manner as in analysis of variance. The sampling distribution underlying Table6 is a product of independent multinomials. According to Bishop, Fienberg and Holland, the kernel of the appropriate likelihood function is the same as that for a simple multinomial or a simple Poisson [7].... In PAGE 10: ... Thus, we do not reject the null hypothesis (H0), and hence conclude that there is no interaction between these two factors. For the remaining hypothesis tests, we selected out only the data for a particular pair of criteria (indicated by the column labeled Hypothesis in Table6 ) and then tested for an interaction between these two by fitting the model described with and without the corresponding fault-type/criterion term. Table 6 summarizes the results of these tests.... In PAGE 10: ... For the remaining hypothesis tests, we selected out only the data for a particular pair of criteria (indicated by the column labeled Hypothesis in Table 6) and then tested for an interaction between these two by fitting the model described with and without the corresponding fault-type/criterion term. Table6 summarizes the results of these tests. The column labeled Hypothesis states the null (H0) and alternative hypothesis (H1) for each test.... In PAGE 10: ... 6. Discussion The three hypotheses in Table6 that tested the effectiveness of each coupling-based criteria against Branch Coverage indicate that the coupling criteria are better at detecting the object-oriented faults used in the experiment. A remaining question is which of the three coupling criteria is the most effective.... ..."
Cited by 3

Table 4: Test of hypothesis 2

in Construction and Evaluation of Social Agents in Hybrid Settings: Approach and
by Martin Meister, Kay Schröter, Diemo Urbig, Eric Lettkemann, Hans-dieter Burkhard
"... In PAGE 12: ...essential factor in shift-plan quality, independent of the individual social types involved. The experimental results clearly disprove this hypothesis, as Table4 shows. The values in this table are the mean of all settings in which one of our social types was involved (excluded are heterogeneous settings because these by definition consist of all social types).... ..."

Table 3. Results of Hypothesis Testing

in Effects of Multimedia on Mobile Consumer Behavior: An Empirical
by Lih-bin Oh, Heng Xu 2003
"... In PAGE 9: ...ontent type was not a significant predictor of entertainment (H6a) at the quot; = 0.01 level, but was significant at quot; = 0.05. However, as hypothesized, content type was a significant positive predictor of informativeness (H6b) and negative predictor for irritation (H6c). Table3 summarizes the results of hypotheses testing. The control variable of coupon proneness was significant for purchase intention.... ..."
Cited by 2
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