商务统计学章节测试课后答案2024春

第十一章测试

1.For the same set of observations on a specified dependent variable, two differentindependent variables were used to develop 2 simple linear regression models.The results are summarized as follows:Based on the above results, we can conclude that
A:a prediction based on Model II is likely better than a prediction based on Model I. B:a prediction based on Model I is likely better than a prediction based on Model II. C:the SSE for Model II is smaller than the SSE for Model I. D:the total variation is different for Model I and Model II.
答案:B
2.A regression analysis between sales (in $1000) and advertising (in $100) yielded the least squares line = 75 + 6x.  This implies that if $800 is spent on advertising, then the predicted amount of sales (in dollars) is
A:$487,500 B:$4,875 C:$123,000 D:$12,300 3.The following results were obtained from a simple regression analysis: = 37.2895 – 1.2024x r2 = 0.6744 and s2 = 0.2934  For each unit change in x, the estimated change in the average value of y is equal to
A:37.289 B:0.6744 C:-1.2024 D:0.2934 4.A regression analysis between sales (in $1,000) and advertising (in $) yielded the least square line  = 80,000 + 5x This implies that an
A:increase of $1 in advertising is expected to result in an increase of $80,005 in sales. B:increase of $1 in advertising is expected to result in an increase of $5 in sales. C:increase of $5 in advertising is expected to result in an increase of $5,000 in sales. D:increase of $1 in advertising is expected to result in an increase of $5,000 in sales. 5.The point estimate of the variance of the error term in a regression model is
A:MSE B: C: D:SSE 6.In a regression problem, if the coefficient of determination is 0.95, this means that:
A:95% of the variation in y can be explained by the variation in x. B:95% of the x values are equal. C:95% of the y values are positive. D:95% of the variation in x can be explained by the variation in y. 7.In regression analysis, the residuals represent the:
A:difference between the actual x values and their predicted values. B:difference between the actual y values and their predicted values. C:change in y per unit change in x. D:square root of the coefficient of determination. 8.In the simple linear regression model, the population parameters of the y-intercept and the slope are estimated by:
A: and B: and C: and  D: and 9.If the standard error of estimate  = 20 and n = 10, then the sum of squares for error, SSE, is:
A:40，000 B:3200 C:400 D:4000 10.Which of the following statistics and procedures can be used to determine whether a linear model should be employed?
A:The coefficient of determination. B:The standard error of estimate. C:The t-test of the slope. D:All of the above are correct answers.