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An Actuary Wanted to Develop a Model to Predict How

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An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and the number of points that the individual's blood pressure exceeded the recommended value (x3). A random sample of 40 individuals was selected. The computer output of the multiple regression model is shown below. An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and the number of points that the individual's blood pressure exceeded the recommended value (x3). A random sample of 40 individuals was selected. The computer output of the multiple regression model is shown below. Is there enough evidence at the 10% significance level to infer that the model is useful in predicting length of life? ______________ enough evidence at the 10% significance level to infer that the model is useful in predicting length of life. Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related. Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related. Is there sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related. What is the coefficient of determination? ______________ Explain: ________________________________________________________ Is there enough evidence at the 10% significance level to infer that the model is useful in predicting length of life?
______________ enough evidence at the 10% significance level to infer that the model is useful in predicting length of life.
Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related?
What is the test statistic?
t = ______________
Conclude:
______________ An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and the number of points that the individual's blood pressure exceeded the recommended value (x3). A random sample of 40 individuals was selected. The computer output of the multiple regression model is shown below. Is there enough evidence at the 10% significance level to infer that the model is useful in predicting length of life? ______________ enough evidence at the 10% significance level to infer that the model is useful in predicting length of life. Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related. Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related. Is there sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related. What is the coefficient of determination? ______________ Explain: ________________________________________________________ .
There ______________ enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related.
Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related?
What is the test statistic?
t = ______________
Conclude:
______________ An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and the number of points that the individual's blood pressure exceeded the recommended value (x3). A random sample of 40 individuals was selected. The computer output of the multiple regression model is shown below. Is there enough evidence at the 10% significance level to infer that the model is useful in predicting length of life? ______________ enough evidence at the 10% significance level to infer that the model is useful in predicting length of life. Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related. Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related. Is there sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related. What is the coefficient of determination? ______________ Explain: ________________________________________________________ .
There ______________ enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related.
Is there sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related?
What is the test statistic?
t = ______________
Conclude:
______________ An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and the number of points that the individual's blood pressure exceeded the recommended value (x3). A random sample of 40 individuals was selected. The computer output of the multiple regression model is shown below. Is there enough evidence at the 10% significance level to infer that the model is useful in predicting length of life? ______________ enough evidence at the 10% significance level to infer that the model is useful in predicting length of life. Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related. Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related. Is there sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related. What is the coefficient of determination? ______________ Explain: ________________________________________________________ .
There ______________ sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related.
What is the coefficient of determination? An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and the number of points that the individual's blood pressure exceeded the recommended value (x3). A random sample of 40 individuals was selected. The computer output of the multiple regression model is shown below. Is there enough evidence at the 10% significance level to infer that the model is useful in predicting length of life? ______________ enough evidence at the 10% significance level to infer that the model is useful in predicting length of life. Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related. Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related. Is there sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related? What is the test statistic? t = ______________ Conclude: ______________ . There ______________ sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death are negatively linearly related. What is the coefficient of determination? ______________ Explain: ________________________________________________________ ______________
Explain:
________________________________________________________

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Yes, there is; 4.068; Reject; is; -1.909...

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