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inferential statistics, survey research - Coggle Diagram
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- inferential statistics 
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- The Null Hypothesis 
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- null hypothesis 
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-  no difference or relationship between parameters in the populations
-  any difference or relationship found for the samples is the result of sampling error.
 
 
 
 
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- types of test 
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- two- tailed test  
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- null hypothesis 
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-  no difference between the groups (A=B)
-  two-tailed test allows for the possibility that a difference may occur in either direction (A>B or B>A)
 
 
 
 
 
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- one-tailed test 
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- null hypothesis: - 
-  one group is not better than another, if a difference occurs it will be in favour of that particular group (A>B)
 
 
 
 
 
 
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- Standard Error  
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- sampling error - if a difference is found between two sample means, the important question is whether the difference is a true or significant one or just the result of sampling error. 
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- normal distribution- 
-   most sample means will be close to the population mean
 
-  very few means are much higher or lower than the population mean
-  mean of all the sample means – good estimate of the population mean
 
 
 
 
 
 
 
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- Test Of Significance 
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- helps on deciding whether to reject the null hypothesis
 infer that the difference is significantly greater than that of chance.
 
 
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- significance of:  
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- T-Test  
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- -determine whether two means are significantly different at a selected probability/significance level
 -look at the p-value, if less than or equal to selected, then there is a statistical difference between the two means
 
 
 
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- Pretest-Posttest 
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-  use t-test for pretest, if the difference is not significant, use t-test on the posttest
-  use t-test for pretest, if the difference is significant, use ANCOVA (analysis of covariance) to adjust posttest scores for initial differences on some variable (in this case the pretest)
 
 
 
 
 
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- Chi Square 
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- compares the proportions actually observed in a study to the proportions expected, to see if they are significantly different 
 
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- simple (One-way) ANOVA 
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- Analysis of Variance  
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- determine whether there is a significant difference between two or more means at a selected probability level 
 
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- look at the probability level associated with F statistic, if less than the preselected, then there the difference is statistically significant 
 
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- survey research 
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- descriptive research- 
-  typical survey studies that assess attitudes, opinions, preferences, demographics, practices, and procedures
 
 
 
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