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Design your empirical research analysis from the class survey. Choose a predicto

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Design your empirical research analysis from the class survey.
Choose a predictor variable (a yes/no or two choice categorical question) and an outcome variable (a Likert scale question)
Submit :
1. Your predictor variable
2. Your outcome variable
3. Your hypothesis about the relationship between the predictor and the outcome.
An example: Predictor: Have you or anyone you know of tested positive for coronavirus?
Outcome: Do you think COVID-19 will be over anytime soon?
Prediction/Hypothesis: I predict that people who say yes to the predictor question will also have higher scores on the outcome. I predict that people who tested positive or know someone who tested positive are more likely to think that the virus will be here longer than people who did not test positive or do not know someone who did.
Hypothesis: predictor: yes. No outcome: Higher lower
Statistical question: Does group 1 on question x have a higher mean on their scores for question 12 than group 2. Analysis: -Use 2 independent groups T test to find the mean difference (difference between the means) between the two groups of the independent/predictor variable across the dependent variable/outcome variable scores.
-Use Pearson Correlation test to see if the variation in one Likert scale variable (predictor) predicts the variation in the other (outcome)? Results:
No matter what test you use, you will get a p score-= “probability” that your result is not statistically significant
p=.05. means there is 5% chance that your results could have occurred randomly (rather than being attributable to the Independent/Predictor variable. Or 5% change that the differences in your Outcome variable result is not statistically significantly created by your Predictor variable.
If p is greater than .05, then we say that the result is not statistically significant. (p=.15, then there is 15% chance that the results are just random and are not tied to the variation of the Independent/predictor variable. Discussion
Critique the study, Errors of interpretation: false positive, false negative
Explain why the hypothesis was not supported… that is was not statistically significant… that it can (not) be generalized…
not enough participants in each group of the Independent/predictor variable. The question was not specific enough…

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