1. Define statistical significance. Why is this important for us to understand? What is the most common significance level in behavioral statistics?

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1. Define statistical significance. Why is this important for us to understand? What is
the most common significance level in behavioral statistics?
2. Define the two types of errors: Type I error and Type II error.
3. What are the eight steps used to test significance. See pages 179 and 180.
4. Using the research article you have been using during this course (or you can find a
new one if you really want to), we are going to look at steps 1-4.
a) Step 1: State the null hypothesis and state the research hypothesis.
b) Step 2: What is the level of risk used in the research article (you will look for the
statistical information and find what value is associated with p).
c) Step 3: What statistical test did they use? It should identify a Pearson r for a
correlational test, a z score for a z test, a t score for a t test, and an F score for an
ANOVA.
d) Step 4: What is the obtained value for the r, z, t, or F score.
e) Steps 7 & 8: Did they reject the null or fail to reject the null hypothesis?
5. Given the following information and setting the level of significance at .05 for decision
making, would your decision be to reject or
to reject the null hypothesis? Why?
a) Age has no effect on mathematical ability (p = .35).
b) Taking aspirin daily does not affect heart attack risk (p < .05).
c) Cats express no food preference based on color (p = .10).
6. Why do we think in terms of "failing to reject" the null rather than just accepting it?
7. What is a confidence interval and how do we calculate it (use the 95% confidence
interval to answer the second part of this question, since that is the most common).
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Transcribed Image Text:1. Define statistical significance. Why is this important for us to understand? What is the most common significance level in behavioral statistics? 2. Define the two types of errors: Type I error and Type II error. 3. What are the eight steps used to test significance. See pages 179 and 180. 4. Using the research article you have been using during this course (or you can find a new one if you really want to), we are going to look at steps 1-4. a) Step 1: State the null hypothesis and state the research hypothesis. b) Step 2: What is the level of risk used in the research article (you will look for the statistical information and find what value is associated with p). c) Step 3: What statistical test did they use? It should identify a Pearson r for a correlational test, a z score for a z test, a t score for a t test, and an F score for an ANOVA. d) Step 4: What is the obtained value for the r, z, t, or F score. e) Steps 7 & 8: Did they reject the null or fail to reject the null hypothesis? 5. Given the following information and setting the level of significance at .05 for decision making, would your decision be to reject or to reject the null hypothesis? Why? a) Age has no effect on mathematical ability (p = .35). b) Taking aspirin daily does not affect heart attack risk (p < .05). c) Cats express no food preference based on color (p = .10). 6. Why do we think in terms of "failing to reject" the null rather than just accepting it? 7. What is a confidence interval and how do we calculate it (use the 95% confidence interval to answer the second part of this question, since that is the most common). MacBook Pro 2$ & 4 7 8. 9. E R. T. Y F G V
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