Can I please have help with these 5 questions? Thanks!

1) A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (w) and number of sit ups a person can do (y). The results of the regression were: y=ax+b a=~1.132 b=30.447 r2=o.s1ssz4 r=6.718 Use this to predict the number of sit ups a person who watches 1.5 hours of TV can do, and please round your answer to a whole number. Z) Statistics students in Oxnard College sampled 9 textbooks in the Condor bookstore and recorded the number of pages in each textbook and its cost. The bivariate data are shown below: Number of Pages (3:) (1054(3)) 759 105.67 956 116.28 810 116.3 508 68.04 772 105.36 404 60.52 09 38.17 7 116.49 89.58 A student calculates a linear model y = ' ' a: +' '. (Please show your answers to two decimal places) Use-the model to estimate the cost when number of pages is 469. Cost = 3' ' (Please show your answer to 2 decimal places.) 3 The data shown below consists of the price (in dollars) of 7 events at a local venue and the number of people who attended. Determine if there is significant negative linear correlation between ticket price and number of attendees. Use a significance level of 0.01 and round all values to 4 decimal places. Ticket Price Attendence Find the Linear Correlation Coefficient r = l Find the p-value p-value = l l The p-value is O Greater than a 0 Less than (or equal to) a The p-value leads to a decision to O Reject Ho 0 Do Not Reject Ho 0 Accept Ho The conclusion is Q There is a significant negative linear correlation between ticket price and attendance. 0 There is a significant linear correlation between ticket price and attendance. 0 There is a significant positive linear correlation between ticket price and attendance. 0 There is insufficient evidence to make a conclusion about the linear correlation between ticket price and attendance. A biologist looked at the relationship between number of seeds a plant produces and the percent of those 'seeds that sprout. The results of the survey are shown below. 58 Elm-\"I 68-6 55-2 a. Find the correlation coefficient: 7" = I I Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: 2 o 3.. a o The p-value is: I (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. 0 There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. O There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful. 0 There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate. 0 There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. d. T2 = (Round to two decimal places) e. Interpret r2 : O 82% of all plants produce seeds whose chance of sprouting is the average chance of sprouting. 0 There is a large variation in the percent of seeds that sprout, but if you only look at plants that produce a fixed number of seeds, this variation on average is reduced by 82%. 0 There is a 82% chance that the regression line will be a good predictor for the percent of seeds that sprout based on the number of seeds produced. 0 Given any group of plants that all produce the same number of seeds, 82% of all of these plants will produce seeds with the same chance of sprouting. f. The \"equation of the linear regression line is: g) = I + :3 (Please show your answers to two decimal places) g. Use the model to predict the percent of seeds that sprout if the plant produces 55 seeds. Percent sprouting = I (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: 0 As x goes up, y goes down. 0 For every additional seed that a plant produces, the chance for each of the seeds to sprout tends to decrease by 0.92 percent. 0 The slope has no practical meaning since it makes no sense to look at the percent of the seeds that sprout since you cannot have a negative number. i. Interpret the y-intercept in the context of the question: 0 The best prediction for a plant that has 0 seeds is 116.25 percent. 0 The average sprouting percent is predicted to be 116.25. 0 If plant produces no seeds, then that plant's sprout rate will be 116.25. 0 The y-intercept has no practical meaning for this study. What is the relationship between the attendance at a major league ball game and the total number of runs scored? Attendance figures (in thousands) and the runs scored for 9 randomly selected games are shown below. ------\" \"an \"II-- a. Find the correlation coefficient: 7' 2 l ' Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: He: = 0 H1: 7e 0 The p-value is: l l (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. 0 There is statistically significant evidence to conclude that there is a correlation between the attendance of baseball games and the runs scored. Thus, the regression line is useful. 0 There is statistically insignificant evidence to conclude that there is a correlation between the attendance of baseball games and the runs scored. Thus, the use of the regression line is not appropriate. 0 There is statistically significant evidence to conclude that a game with higher attendance will have fewer runs scored than a game with lower attendance. 0 There is statistically significant evidence to conclude that a game with a higher attendance will have more runs scored than a game with lower attendance. d. 1'2 = (Round to two decimal places) (Round to two decimal places) e. Interpret r2 : O 62% of all games will have the average number of runs scored. 0 Given any fixed attendance, 62% of all of those games will have the predicted number of runs scored. 0 There is a 62% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game. 0 There is a large variation in the runs scored in baseball games, but if you only look at games with a fixed attendance, this variation on average is reduced by 62%. f. The equation of the linear regression line is: Q = l l + l :1: (Please show your answers to two decimal places) g. Use the model to predict the runs scored at a game that has an attendance of 28,000 people. Runs scored = l I (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: 0 For every additional thousand people who attend a game, there tends to be an average increase of 0.17 runs scored. 0 The slope has no practical meaning since the total number runs scored in a game must be positive. 0 As x goes up, y goes up. i. Interpret the y-intercept in the context of the question: 0 If the attendance of a baseball game is 0, then 2 runs will be scored. 0 The y-intercept has no practical meaning for this study. 0 The average runs scored is predicted to be 2. O The best prediction for a game with 0 attendance is that there will be 2 runs scored