answer all questions.
The sample mean of the dependent and independent variables satisfy the estimated OLS sample regression line.
No perfect multicollinearity among explanatory variables.
The conditional variance of the dependent variable on the explanatory variables is constant.
Standard error of the regression is used to estimate the standard errors of the corresponding OLS regressors.
Perfect collinearity between explanatory variables.
Mean conditional independence of the error term.
Error term conditional on the explanatory variables of the regression model is normally distributed.
The zero conditional expectation of the error term on the explanatory variables.
The zero correlation between the fitted values and the residuals of a multiple regression model.
A random sample of the dependent and explanatory variables of a regression model is available.
1. Assumption of the classical linear regression model.
2. Not an assumption of the classical linear regression model.
answer all questions.
The sample mean of the dependent and independent variables satisfy the estimated OLS sample regression line.
No perfect multicollinearity among explanatory variables.
The conditional variance of the dependent variable on the explanatory variables is constant.
Standard error of the regression is used to estimate the standard errors of the corresponding OLS regressors.
Perfect collinearity between explanatory variables.
Mean conditional independence of the error term.
Error term conditional on the explanatory variables of the regression model is normally distributed.
The zero conditional expectation of the error term on the explanatory variables.
The zero correlation between the fitted values and the residuals of a multiple regression model.
A random sample of the dependent and explanatory variables of a regression model is available.
1. Assumption of the classical linear regression model.
2. Not an assumption of the classical linear regression model.
Related textbook solutions
Related questions
Question 1
Which of the following approaches to understanding and predicting consumer behavior depends primarily on the knowledge and experience of a firm's employees and its suppliers?
| Test marketing and price experiments | ||
| Analysis of historical data. | ||
| Direct consumer surveys. | ||
| Expert opinion. |
Question 2
In which of the following situations would reliance on expert opinion as a basis for a managerial decision be most preferred?
| When the product being marketed is relatively new. | ||
| When the level of economic activity can have a significant effect on the demand for the firm's output. | ||
| When the product can be packaged with a variety of price and quality combinations. | ||
| When the business in question serves as a supplier of inputs to other businesses, especially in multi-product situations where other strategies may be prohibitively expensive. |
Question 3
The approach to analyzing consumer behavior that asks consumers to rank and choose among different product attributes to reveal their relative valuation of different characteristics is called:
| conjoint analysis. | ||
| contingent valuation. | ||
| the hedonic estimation technique. | ||
| a direct consumer survey. |
Question 4
All of the following are limitations of direct consumer surveys except:
| the possibility of response biases because survey respondents may not want to reveal their true preferences. | ||
| the possibility that the type of questions asked may unintentionally bias the respondent's answers. | ||
| the likelihood that respondents will deliberately and systematically mislead interviewers. | ||
| the possibility that consumers' responses may not reflect their actual behavior in the market place. |
Question 5
Which of the following approaches to understanding and predicting consumer behavior does not actually solicit any information from potential customers?
| Expert opinion. | ||
| Test marketing. | ||
| Analysis of historical data. | ||
| Conjoint analysis. |
Question 6
Data collected on a sample of individuals with different characteristics at a specific point in time are called:
| panel data. | ||
| cross-section data. | ||
| time series data. | ||
| none of the above. |
Question 7
Which of the following approaches to understanding and predicting consumer behavior provides the most insight into how consumers can be expected to respond in an actual market setting?
| Test marketing. | ||
| Conjoint analysis. | ||
| Expert opinion. | ||
| Analysis of historical data. |
Question 8
An approach to analyzing consumer behavior in which consumer reaction to different prices is analyzed in a laboratory situation or a test market is called:
| non-price experiments. | ||
| focus groups. | ||
| price experiments. | ||
| none of the above. |
Question 9
Data collected on the same observation unit at a number of points in time are called:
| panel data. | ||
| time series data. | ||
| cross-section data. | ||
| none of the above. |
Question 10
A measure of how much the coefficient would vary in regressions based on different samples is called:
| F-statistic. | ||
| standard error of the estimated coefficient. | ||
| t-statistic. | ||
| partial F-statistic. |
Question 11
The test statistic used to test the hypothesis of whether a regression coefficient is significantly different from zero, holding all other independent variables constant, is called a(n):
| t-test. | ||
| F-test. | ||
| multicollinearity test. | ||
| autocorrelation test. |
Question 12
Regression analysis that analyzes the relationship between one dependent variable and several independent variables is called:
| cluster analysis. | ||
| correlation analysis. | ||
| multiple regression analysis. | ||
| simple regression analysis. |
Question 13
The ratio of the regression coefficient to its standard error is called:
| F-statistic. | ||
| t-statistic. | ||
| coefficient of determination. | ||
| partial F-statistic. |
Question 14
The coefficient of determination will range between what values?
| -1 and +1 | ||
| 0 and 1 | ||
| -3 and +3 | ||
| none of the above |
Question 15
The range of values in which we can be confident that the true regression coefficient lies within a given degree of probability is called a:
| confidence interval. | ||
| logistic regression. | ||
| prediction interval. | ||
| none of the above. |
Question 16
The estimated regression equation is Y = 10 + 2.5X, if X =0 than the predicted value of Y is equal to
| 2.5 | ||
| 7.5 | ||
| 12.5 | ||
| 10 |
