e.com/courses/3345310/assignments/33452124?module_item_id=74932825 Question 32 10% of all Americans suffer from sleep apnea. A researcher suspects that a lower percentage of those who live in the inner city have sleep apnea. Of the 319 people from the inner city surveyed, 26 of them suffered from sleep apnea. What can be concluded at the level of significance of a = 0.017 a. For this study, we should use | Select an answer b. The null and alternative hypotheses would be: Ho: 7 \\ Select an answer V (please enter a decimal) H,: 2 v Select an answer Please enter a decimal) C. The test statistic ? = (please show your answer to 3 decimal places.) d. The p-value = (Please show your answer to 4 decimal places.) e. The p-value is ?v a f. Based on this, we should | Select an answer V | the null hypothesis. g. Thus, the final conclusion is that ... The data suggest the population proportion is not significantly smaller than 10% at o = 0.01, so there is sufficient evidence to conclude that the population proportion of inner city residents who have sleep apnea is equal to 10%. The data suggest the populaton proportion is significantly smaller than 10% at c = 0.01, so there is sufficient evidence to conclude that the population proportion of inner city residents who have sleep apnea is smaller than 10% The data suggest the population proportion is not significantly smaller than 10% at a = 0.01, so there is not sufficient evidence to conclude that the population proportion of inner city residents who have sleep apnea is smaller than 10%. h. Interpret the p-value in the context of the study. There is a 13.54% chance that fewer than 10% of all inner city residents have sleep apnea. There is a 10% chance of a Type | error If the population proportion of inner city residents who have sleep apnea is 10% and if another 319 inner city residents are surveyed then there would be a 13.54% chance fewer than 8% of the 319 residents surveyed have sleep apnea. If the sample proportion of inner city residents who have sleep apnea is 8% and if another 319 inner city residents are surveyed then there would be a 13.54% chance of concluding that fewer than 10% of inner city residents have sleep apnea. i. Interpret the level of significance in the context of the study. If the population proportion of inner city residents who have sleep apnea is 10% and if another 319 inner city residents are surveyed then there would be a 1% chance that we would end up falsely concluding that the proportion of all inner city residents who have sleep apnea is smaller than 10%. There is a 1% chance that the proportion of all inner city residents who have sleep apnea is smaller than 10%. There is a 1% chance that aliens have secretly taken over the earth and have cleverly disguised themselves as the presidents of each of the countries on earth. If the population proportion of inner city residents who have sleep apnea is smaller than 10% and if another 319 inner city residents are surveyed then there would be a 1% chance that we would end up falsely concluding that the proportion of all inner city residents who have sleep apnea is equal to 10%. Hint: Help Helpful Videos: Calculations [-] Setup [-] Interpretations [+]ments/33452124?module_item_id=74932825 Question 33 What is the relationship between the Previous exam scores? The results of the survey are shown below. Ine statistics students study per week and their final Time 7 0 5 7 13 7 2 Score 76 65 73 74 100 70 70 82 a. Find the correlation coefficient: T : Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: 7v -0 The p-value is: (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. There is statistically insignificant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. There is statistically significant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. There is statistically insignificant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the use of the regression line is not appropriate. There is statistically significant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the regression line is useful. d. 72. (Round to two decimal places) e. Interpret ' : Given any group that spends a fixed amount of time studying per week, 77% of all of those students will receive the predicted score on the final exam. 77% of all students will receive the average score on the final exam. There is a large variation in the final exam scores that students receive, but if you only look at students who spend a fixed amount of time studying per week, this variation on average is reduced by 77%. There is a 77% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. The equation of the linear regression line is: I (Please show your answers to two decimal places) 3. Use the model to predict the final exam score for a student who spends 9 hours per week studying. Final exam score - (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: The slope has no practical meaning since you cannot predict what any individual student will score on the final. For every additional hour per week students spend studying, they tend to score on averge Z.44 higher on the final exam. As x goes up, y goes up. i. Interpret the y-intercept in the context of the question: If a student does not study at all, then that student will score 62 on the final exam. The y-intercept has no practical meaning for this study. The best prediction for a student who doesn't study at all is that the student will score 62 on the final exam. The average final exam score is predicted to be 62ghtingale.instructure.com/courses/3345310/assignments/33452124?module_item_id=749 Question 37 You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 25 35 21 19 62 35 72 18 22 30 29 35 Ho: p - 0 Ha: p - 0 Find the Linear Correlation Coefficient Find the p-value p-value - The p-value is Greater than a Less than (or equal to) a The p-value leads to a decision to O Reject Ho Do Not Reject Ho O Accept Ho The conclusion is There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. There is a significant positive linear correlation between driver age and number of driver deaths There is a significant linear correlation between driver age and number of driver deaths. There is a significant negative linear correlation between driver age and number of driver deaths Hint: Helpful Video on the Linear Regression Line Helpful Video on Correlation Helpful Video on Hypothesis Tests for Correlation Hints Submit QuestionQuestion 10 The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. 8 11.5 6.7 3.6 2.5 2.7 2.2 0.6 13.9 10.9 9.5 7.4 6.1 5.7 4.7 - thousands of automatic weapons y - murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 3.9 thousand automatic weapons? Answer - Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 9.3 thousand automatic weapons ? Answer - Round to 3 decimal places. Hint: Help Submit Question052?module_item_id=74932680 Question 1 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 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 125 10 133 14 123 18 112 22 95 26 178 30 145 34 141 Ho: p = 0 Ha: p = 0 Find the Linear Correlation Coefficient Find the p-value p-value = The p-value is Greater than a O Less than (or equal to) a The p-value leads to a decision to Reject Ho Do Not Reject Ho Accept Ho The conclusion is There is a significant positive linear correlation between ticket price and attendance. There is insufficient evidence to make a conclusion about the linear correlation between ticket price and attendance. There is a significant linear correlation between ticket price and attendance. There is a significant negative linear correlation between ticket price and attendance. Hint: Helpful Video on the Linear Regression Line _ (-] Helpful Video on Correlation [+1