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1. At 0.01 level of significance, test the claim that there is significant difference in the weight in September of male and female respondents. Assume the data are normally distributed. (5pts) a. Claim: b. Ho: Ha: C. Test: Tail: Level of significance: d. Decision Rule: e. p-value: f. Decision: g. Conclusion: 2. At 0.05 level of significance, test the claim that there is significant difference in the weight in April of male and female respondents. Assume the data are normally distributed. (5pts) 3. At 0.01 level of significance, test the claim that there is significant difference in the BMI in September of male and female respondents. Assume the data are normally distributed. (5pts) . At 0.05 level of significance, test the claim that there is significant difference in the BMI in April of male and female respondents. Assume the data are normally distributed. (5pts) 5. At 0.01 level of significance, test the claim that weight in September is greater than the weight in April of the respondents. Assume the data are normally distributed. (5pts) 5. At 0.05 level of significance, test the claim that BMI in September is greater than the BMI in April of the respondents. Assume the data are normally distributed. (5pts) 7. Determine whether there is significant linear correlation between the weight in September and April. Use a=0.05. (5pts) 8. Determine whether there is significant linear correlation between the BMI in September and April. Use a=0.05. (5pts) 9. Fit the linear regression equation that expresses weight in September (Y) and weight in April (X). Interpret the slope, intercept and coefficient of determination. (5pts) 10. Fit the linear regression equation that expresses BMI in September (Y) and BMI in April (X). Interpret the slope, intercept and coefficient of determination. (5pts)H C G K A Marital Status Educational Level Smoking Status Weight in September Weight in April BMI in September BMI in April 59 22.02 18.14 19.70 17.4 4.09 22.43 HNNP 26.97 25.43 21.51 20 10 18.69 17.40 24.24 22.8 21.23 20.23 10.26 29.24 21.8 21.02 7.63 16.89 24.5 23.85 - EE 20.68 20.15 20.97 20.36 17.30 26.73 13.30 22.8 19.48 19.24 24.7 24.69 20.6 20.79 20.4 20.60 21.0 21.24 18.37 18.53 22.40 22.61 28.17 28.43 3.60 23.81 26.57 26.78 18.89 18 27 19.31 19.75 20.98 21.32 21.78 22.22 19.78 20.23 12.40 22.82 22.76 23.19 20.15 20.69 22.14 22.57 20.27 20.76 22.15 22.93 23.87 24.67 18.61 19.34 21.73 22.58 18.93 19.72 25.88 26.72 28.5 29.53 - E - EEEEE 21.8 22.79 18.31 19.28 19.64 20.63 23.02 14.10 :0.63 21.91 22.61 23.81 :2.03 23.42 20.31 21.43 20.31 21.36 19.5 20.77 21.05 22.31 23.47 25.11 22.84 24.29 NNWNNWNH 19.50 20.90 18.51 19.83 21.40 22.97 3 3 17.72 19.42E H L M Instruction: Perform the following in Excel. Place your solutions in the space provided or each question. The following data shows the Health Exam Results of 60 randomly selected individuals. The following variables are gathered: 1. "Sex" is listed as male (M] or female (F) 2. "Marital status" values are defined as follows: M = married S = single W = widowed 10 D = divorced 11 3. "Age" is given in years. 12 4. "Educational level" values are defined as follows 13 0 = no high school degree 14 1 = high school graduate 15 2 = college graduate 16 3 = college degree 17 5. "Smoking status" values are defines as follows: 18 0 = does not smoke 19 1 = smoke less than one pack per day 20 2 = smoke one or more than one pack per day 21 6. "Weight in September" is given in ka 22 7. "Weight in April" is given in ka 23 8. "BMI in September" 24 9. "BMI in April' 25 26 Questions 27 1. At 0.01 level of significance, test the claim that there is significant difference in the weight in September of male and female respondents. Assume the data are normally distributed. [5pts] 28 2. At 0.05 level of significance, test the claim that there is significant difference in the weight in April of male and female respondents. Assume the data are normally distributed. (5pts] 29 3. At 0.01 level of significance, test the claim that there is significant difference in the BMI in September of male and female respondents. Assume the data are normally distributed. (5pts) 30 4. At 0.05 level of significance, test the claim that there is significant difference in the BMI in April of male and female respondents. Assume the data are normally distributed. (5pts) 31 5. At 0.01 level of significance, test the claim that weight in September is greater than the weight in April of the respondents. Assume the data are normally distributed. (5pts) 32 6. At 0.05 level of significance, test the claim that BMI in September is greater than the BMI in April of the respondents. Assume the data are normally distributed. (5pts] EE 7. Determine whether there is significant linear correlation between the weight in September and April. Use a=0.05. [5pts) 34 8. Determine whether there is significant linear correlation between the BMI in September and April. Use a=0.05. (5pts) 35 9. Fit the linear regression equation that expresses weight in September (Y) and weight in April (X]. Interpret the slope, intercept and coefficient of determination. (Spts) 36 10. Fit the linear regression equation that expresses BMI in September [Y] and BMI in April (X]. Interpret the slope, intercept and coefficient of determination. [Spts] 37