Which of the following is the alternative hypothesis? Group of answer choices Ha: There is a linear relationship between Sale amount and Tip. Ha: There is a positive linear relationship between Sale amount and Tip. Ha: There is a negative linear relationship between Sale amount and Tip. Ha: There is no linear relationship between Sale amount and Tip.

Statistics Question

1. A professor is interested in how attendance is related to grades her class. She goes through her records and determines each student’s final average and the number of days absent. The scores for her sample are given in the table below. a. Construct a scatter plot of the relationship between final averages and the number of days absent. b. Is there a significant relationship between final averages and the number of days absent? Calculate and interpret the correlation and report it in proper APA format. c. Compute r2 for the data. What percent of the variability in final averages is accounted for by the number days absent?

Listed below are amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.01. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) 31.80 52.94 85.82 102.16 60.17 111.77 D 5.46 6.07 15.82 15.40 11.15 20.32 Construct a scatterplot. Choose the correct graph below. O A. O B. Oc. D. Q 25- 25- 25 0- 30 0- 30 Bill Amount ($) 0+ 30 Bill Amount (S) 0- 30 Bill Amount (S) 120 120 120 Bill Amount (S) 120 The linear correlation coefficient is r= 0.954 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: p H,: P (Type integers or decimals. Do not round.) Tip Amount ($) ip Amount ($) Tip Amount ($) Tip Amount ($)

An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)

Listed below are the amounts of bills for dinner and the amounts of the tips that were left. Construct a​ scatterplot, find the value of the linear correlation coefficient​ r, and find the​ P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of α=0.01. If everyone were to tip with the same​ percentage, what should be the value of​ r?   Bill​ (dollars) 31.65 53.83 87.10 103.64 60.34 109.80   Tip​ (dollars) 3.74 5.76 14.73 16.86 7.44 20.73   1. The linear correlation coefficient is r=   2.  What are the null and alternative​ hypotheses?   3. The test statistic is t=   4. The P-Value is P=

even though we may observe a strong relationship between the explanatory and response variables, a lurking variable may also influence the response vatiabke. This is reffered to as A. correlation  B. confounding C.association  D. causation

At the .05 significance level, does the data below show significant correlation? x y 3 12.87 4 13.66 5 17.95 6 23.44 7 15.93 8 13.62 9 27.91

The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of a=0.05. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. A. 20- 20 E 70 OB. 70- 20+ 20 70 Best Actress (years) The linear correlation coefficient is r= (Round to three decimal places as nee Best Actress (years) Best Actresses and Best Actors Best Actress 28 31 30 64 31 Best Actor 44 39 37 43 49 33 46 47 56 OC. COD. Q 70- 20 20 Best Actress (years) 30 59 23 42 53 442 52 39 56 44 34 70 20 20 70 Best Actress (years)

The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of a = 0.01. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. OA. 70- Best Actor (years) 20+ 20 Q [ 70 Best Actress (years) The linear correlation coefficient is r= ☐ (Round to three decimal places as needed.). B. OC. Q 70- 70- Q 20- 20 20- 70 20 70 Best Actress (years) Best Actress (years) Best Actresses and Best Actors Best Actress 29 29 28 57 31 32 45 28 63 22 42 51D Best Actor 45 39 39 47 51 49 64 48 38 55 43 34 O D. 70- Q G 20 20 70 Best Actress (years)