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7.36 Beer and blood alcohol content: Many people believe that gender, weight, drinking habits, and many other factors are much more important in predicting blood alcohol content (BAC) than simply considering the number of drinks a person consumed. Here we examine data from sixteen student volunteers at Ohio State University who each drank a randomly assigned number of cans of beer. These students were evenly divided between men and women, and they differed in weight and drinking habits. Thirty minutes later, a police officer measured their blood alcohol content (BAC) in grams of alcohol per deciliter of blood (Malkevitc and Lesser, 2008). The scatterplot and regression table summarize the ofindings. BAC (grams per deciliter) 0.15- 0.10- 0.05- 0 2 (Intercept) beers 0 0 0 0 Estimate -0.0127 0.0180 0 0 0 0 0 0 6 Cans of beer 8 0 -∞ 8 Std. Error t value P(>|t|) 0.0126 -1.00 0.3320 0.0024 7.48 0.0000 0 (a) Describe the relationship between the number of cans of beer (x) and BAC (y). O moderate/strong, negative Oweak, positive Omoderate/strong, positive O weak, negative (b) Write the equation of the regression line. Interpret the slope and intercept in context. The equation of the regression line is (please do not round): ŷ + x The interpretation of the slope is: O For each additional can of beer, BAC is expected to increase by about .018 O For each additional can of beer, BAC is expected to increase by about .0127 O For each additional can of beer, BAC is expected to decrease by about .018 O For each additional can of beer, BAC is expected to decrease by about .0127

7.36 Beer and blood alcohol content: Many people believe that gender, weight, drinking habits, and many other factors are much more important in predicting blood alcohol content (BAC) than simply considering the number of drinks a person consumed. Here we examine data from sixteen student volunteers at Ohio State University who each drank a randomly assigned number of cans of beer. These students were evenly divided between men and women, and they differed in weight and drinking habits. Thirty minutes later, a police officer measured their blood alcohol content (BAC) in grams of alcohol per deciliter of blood (Malkevitc and Lesser, 2008). The scatterplot and regression table summarize the ofindings. BAC (grams per deciliter) 0.15- 0.10- 0.05- 0 2 (Intercept) beers 0 0 0 0 Estimate -0.0127 0.0180 0 0 0 0 0 0 6 Cans of beer 8 0 -∞ 8 Std. Error t value P(>|t|) 0.0126 -1.00 0.3320 0.0024 7.48 0.0000 0 (a) Describe the relationship between the number of cans of beer (x) and BAC (y). O moderate/strong, negative Oweak, positive Omoderate/strong, positive O weak, negative (b) Write the equation of the regression line. Interpret the slope and intercept in context. The equation of the regression line is (please do not round): ŷ + x The interpretation of the slope is: O For each additional can of beer, BAC is expected to increase by about .018 O For each additional can of beer, BAC is expected to increase by about .0127 O For each additional can of beer, BAC is expected to decrease by about .018 O For each additional can of beer, BAC is expected to decrease by about .0127

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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7.36 Beer and blood alcohol content: Many people believe that gender, weight, drinking habits, and many other factors are much more important in predicting blood alcohol content (BAC) than simply considering the number of drinks a person consumed. Here we examine data from sixteen student volunteers at Ohio State University who each drank a randomly assigned number of cans of beer. These students were evenly divided between men and women, and they differed in weight and drinking habits. Thirty minutes later, a police officer measured their blood alcohol content (BAC) in grams of alcohol per deciliter of blood (Malkevitc and Lesser, 2008). The scatterplot and regression table summarize the ofindings. BAC (grams per deciliter) ŷ 0.15- = 0.10- 0.05- 0 EN 2 (Intercept) beers 0 0 0 0 Estimate -0.0127 0.0180 0 0 0 0 0 4 6 Cans of beer 0 0.0126 0.0024 8 0 -∞ 8 Std. Error t value P(>|t|) -1.00 0.3320 7.48 0.0000 (a) Describe the relationship between the number of cans of beer (x) and BAC (y). O moderate/strong, negative weak, positive O moderate/strong, positive O weak, negative (b) Write the equation of the regression line. Interpret the slope and intercept in context. The equation of the regression line is (please do not round): + 0 x The interpretation of the slope is: O For each additional can of beer, BAC is expected to increase by about .018 O For each additional can of beer, BAC is expected to increase by about .0127 For each additional can of beer, BAC is expected to decrease by about .018 For each additional can of beer, BAC is expected to decrease by about .0127
Transcribed Image Text:7.36 Beer and blood alcohol content: Many people believe that gender, weight, drinking habits, and many other factors are much more important in predicting blood alcohol content (BAC) than simply considering the number of drinks a person consumed. Here we examine data from sixteen student volunteers at Ohio State University who each drank a randomly assigned number of cans of beer. These students were evenly divided between men and women, and they differed in weight and drinking habits. Thirty minutes later, a police officer measured their blood alcohol content (BAC) in grams of alcohol per deciliter of blood (Malkevitc and Lesser, 2008). The scatterplot and regression table summarize the ofindings. BAC (grams per deciliter) ŷ 0.15- = 0.10- 0.05- 0 EN 2 (Intercept) beers 0 0 0 0 Estimate -0.0127 0.0180 0 0 0 0 0 4 6 Cans of beer 0 0.0126 0.0024 8 0 -∞ 8 Std. Error t value P(>|t|) -1.00 0.3320 7.48 0.0000 (a) Describe the relationship between the number of cans of beer (x) and BAC (y). O moderate/strong, negative weak, positive O moderate/strong, positive O weak, negative (b) Write the equation of the regression line. Interpret the slope and intercept in context. The equation of the regression line is (please do not round): + 0 x The interpretation of the slope is: O For each additional can of beer, BAC is expected to increase by about .018 O For each additional can of beer, BAC is expected to increase by about .0127 For each additional can of beer, BAC is expected to decrease by about .018 For each additional can of beer, BAC is expected to decrease by about .0127
(c) Do the data provide strong evidence that drinking more cans of beer is associated with an increase in blood alcohol? State the null and alternative hypotheses, report the p-value, and state your conclusion. The hypotheses are: Ho: Number of cans of beer drank is a significant predictor of BAC Ha: Number of cans of beer drank is not a significant predictor of BAC O Ho: The more beer drank, the higher someone's BAC Ha: The more cans of beer drank, the lower the BAC Ho: Number of cans of beer drank is not a significant predictor of BAC Ha: Number of cans of beer drank is a significant predictor of BAC The p-value for the test is: p≈ The result of this hypothesis test is: the more cans of beer you drink, the higher your BAC number of cans of beer drank is a significant predictor of BAC number of cans of beer drank is not a significant predictor of BAC (d) The correlation coefficient for number of cans of beer and BAC is 0.89. Calculate R² and interpret it in context. The value of R² is (please leave your answer as a decimal, and round to three places) The interpretation of the value above is: O the percent of time that our model is accurate O the proportion of alcohol in beer that contributes to BAC O the proportion of variation in BAC that is explained by number of cans of beer consumed
Transcribed Image Text:(c) Do the data provide strong evidence that drinking more cans of beer is associated with an increase in blood alcohol? State the null and alternative hypotheses, report the p-value, and state your conclusion. The hypotheses are: Ho: Number of cans of beer drank is a significant predictor of BAC Ha: Number of cans of beer drank is not a significant predictor of BAC O Ho: The more beer drank, the higher someone's BAC Ha: The more cans of beer drank, the lower the BAC Ho: Number of cans of beer drank is not a significant predictor of BAC Ha: Number of cans of beer drank is a significant predictor of BAC The p-value for the test is: p≈ The result of this hypothesis test is: the more cans of beer you drink, the higher your BAC number of cans of beer drank is a significant predictor of BAC number of cans of beer drank is not a significant predictor of BAC (d) The correlation coefficient for number of cans of beer and BAC is 0.89. Calculate R² and interpret it in context. The value of R² is (please leave your answer as a decimal, and round to three places) The interpretation of the value above is: O the percent of time that our model is accurate O the proportion of alcohol in beer that contributes to BAC O the proportion of variation in BAC that is explained by number of cans of beer consumed
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