Week 9 - Discussion questions

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Toronto Metropolitan University *

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100

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Statistics

Date

Feb 20, 2024

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docx

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Uploaded by MatePheasantMaster81

Week 9 Discussion Questions 1. Rank the following correlation coefficients on strength of their relationship (list the weakest first). +0.71 (5) +0.36 (1) -0.45 (2) +0.47 (3) -0.62 (4) 2. Based on the scatterplot below, are X and Y correlated? Explain. There is a link between the variables, they are adversely connected, when one goes up, the other goes down. 3. The coefficient of determination between two variables is .64. Answer the following questions: a. What is the Person correlation coefficient? r = 0.64 = 0.8 b. How strong is the relationship? r > 0.75, the relationship is very strong. c. How much of the variance in the relationship between these two variables is unaccounted for? p = 100% - 64% = 36% 4. Provide three examples of an association between two variables where a casual relationship makes perfect sense conceptually but since correlations do not imply causality makes little sense statistically until further examination? The rise in fast food sales and homeliness rate. Even though both rose together, that doesn’t mean that the rise in fast food sales caused homeliness. 5. A study examined the relationship between coffee consumption and level of stress for a group of 50 undergraduates. The correlation was 0.373 and a two-tailed test of significance was conducted at the 0.05 level of significance and revealed a P-value was 0.01. First, is the correlation significant? Second, what’s wrong with the following statement: “As a result of the data collected in this study and our rigorous analyses, we have concluded that if you drink less coffee, you will experience less stress”? There is a significant correlation between the variables, which means that the “if you drink more coffee, you will experience less stress” sentence is wrong. 6. What type of statistical test would you use if the research question was:

a. Is milk (mL) intake related to a child’s bone density (continuous measure)? Pearson’s correlation coefficient test because both variables are continuous. b. Is an individual’s happiness (IV - likert scale: unhappy, somewhat unhappy, neither unhappy or happy, somewhat happy, happy) associated with the amount of income (DV - $ as a continuous variable) they make? ANOVA test. c. Is weight status (severely underweight, underweight, normal weight, overweight and obese) related to employment (Yes/No)? logistic regression test.

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