1. What type of analysis is this?

a. Two-sample t-test

b. Paired t-test

c. Simple linear regression

d. Multiple linear regression

e. Contingency table analysis

2.What are the independent and dependent variables?

a. Dependent variable is unknown, independent variable = body temperature

b. Dependent variable is unknown, independent variable = heart rate

c. Dependent variable = heart rate, independent variable = body temperature

d. Dependent variable = body temperature, independent variable = heart rate

e. Variable order does not matter here, i.e. (x, y) is the same as (y, x).Either body temperature or heart rate can be the independent variable. The other is then the dependent variable.

3.What are the most appropriate null and alternative hypotheses for this analysis?

a. H0: b0 = 0, H1: b0 ≠ 0

b. H0: b1 = 0, H1: b1 ≠ 0

c. H0: β 0 = 0, H1: β 0 ≠ 0

d. H0: β 1 = 0, H1 β 1 ≠ 0

e. H0: ρ = 0, H1: ρ ≠ 0

4.What is the size of our sample?

a. 1

b. 128

c. 129

d. 130

e. Cannot be determined from the given information

InformationFor questions 8-18, refer to the following Information: In their 1992 JAMA article &quot;A Critical Appraisal of 98.Degrees F, the Upper Limit of the Normal Body Temperature, and Other Legacies of Carl Reinhold AugustWunderlich,&quot; Mackowiak, Wasserman and Levine examined whether body temperatures (degrees Fahrenheit)can be predicted by heart rate (beats per minute). Think about it. When you have a fever, do you have ahigher heart rate? Could a higher heart rate be a mechanism of the body to generate higher bodytemperatures? The researchers generated the following results using SAS software; however, they do notknow how to interpret any of the output. Confident of your statistical abilities, they have come to you withtheir output and a list of questions. It’s now your job to help them interpret their output. Don’t let them down!Analysis of VarianceSum ofMeanSourceDFsquaressquareF ValuePr &gt; FTapow4.461764.461768.800.8036Error12864 .88316CCorrected Total129BRoot MSE0.71197R-Square0.0643Dependent Mean98 .24923Adi R-Sa0.0570Coeff var0.72466Parameter EstimatesParameterStandardVariableDFEstimateErrort ValuePr &gt; Itl95% Confidence LimitsIntercept96.306758.65770146.43&lt;.000195.0053897 . 60813HR0.026338. 00888D8. 00360.808770. 84390