The t – distribution is similar to the standard normal distribution in the following ways except: A. The spread of the t – distribution varies, depending on the degrees of freedom. B. It is symmetrical about the mean. C. The mean, median, and mode are all equal to zero and are located at the center of the distribution. D. The curve is bell-shaped and is asymptotic to the horizontal axis. The proportion of variation of the dependent variable Y explained by its linear relationship with an independent variable, or set of independent variables, is determined by meansof the A. Correlation coefficient B. Regression coefficients C. Estimate of the population proportion D. Coefficient of Variation The correlation coefficient computed for the relationship between dependent variable Y and independent variable X is – 0.35. This result means that A. 35% of the variation of the dependent variable Y is due to the linear relationship between Y and X. B. 12.25% of the variation of the dependent variable Y is due to the linear relationship between Y and X. C. there is a weak, negative relationship between Y and X. D. there is a very weak, negative relationship between Y and X. When three experimental groups were compared using the one-way Analysis of Variance(ANOVA), the result turned out to be significant, that is, the Ho was rejected. What will be the corresponding interpretation of this result? A. All three experimental groups significantly differ in means or they have different effects on the dependent variable. B. Exactly two of the three groups significantly differ. C. At least two of the three experimental groups significantly differ in means or in terms of their effect on the dependent variable. D. None of the above. When data on a dependent or response variable is classified based on different levels of two factors or criterion, the data set-up is appropriate for a: A. One-way Analysis of Variance B. Two-Way Analysis of Variance C. Randomized Complete Block Design ANOVA D. Multiple pairwise t-tests Which of the following is not a purpose of simple linear regression analysis? A. Predict dependent variable Y in terms of an independent variable X. B. Explain some of the variability of the dependent variable Y due to the relationship between Y and an independent variable X. C. Compare the response variable Y and the predictor variable X. D. Describe the dependence of the response variable Y on the predictor variable X. A manufacturer claims that a particular automobile will get at least 50 miles per gallon on the highway. The researchers at a consumer-oriented magazine plans to test this claim with a simple random sample of 30 cars. Assuming that the standard deviation between individual cars is 2.3 miles per gallon, what should the researchers conclude if the sample mean is 49 miles per gallon? A. There is not sufficient evidence to reject the manufacturer’s claim; 49 miles per gallon is too close to the claimed 50 miles per gallon. B. The manufacturer’s claim should not be rejected because the p-value of 0.0086 is too small. C. The manufacturer’s claim should be rejected because the sample mean is less than the claimed mean. D. The p-value of 0.0086 is sufficient evidence to reject the manufacturer’s claim.
The t – distribution is similar to the standard normal distribution in the following ways except:
A. The spread of the t – distribution varies, depending on the degrees of freedom.
B. It is symmetrical about the mean.
C. The mean, median, and
D. The curve is bell-shaped and is asymptotic to the horizontal axis.
The proportion of variation of the dependent variable Y explained by its linear relationship with an independent variable, or set of independent variables, is determined by meansof the
A.
B. Regression coefficients
C. Estimate of the population proportion
D. Coefficient of Variation
The correlation coefficient computed for the relationship between dependent variable Y and independent variable X is – 0.35. This result means that
A. 35% of the variation of the dependent variable Y is due to the linear relationship between Y and X.
B. 12.25% of the variation of the dependent variable Y is due to the linear
relationship between Y and X.
C. there is a weak, negative relationship between Y and X.
D. there is a very weak, negative relationship between Y and X.
When three experimental groups were compared using the one-way Analysis of Variance(ANOVA), the result turned out to be significant, that is, the Ho was rejected. What will be the corresponding interpretation of this result?
A. All three experimental groups significantly differ in means or they have different effects on the dependent variable.
B. Exactly two of the three groups significantly differ.
C. At least two of the three experimental groups significantly differ in means or in terms of their effect on the dependent variable.
D. None of the above.
When data on a dependent or response variable is classified based on different levels of two factors or criterion, the data set-up is appropriate for a:
A. One-way Analysis of Variance
B. Two-Way Analysis of Variance
C. Randomized Complete Block Design ANOVA
D. Multiple pairwise t-tests
Which of the following is not a purpose of simple linear
A. Predict dependent variable Y in terms of an independent variable X.
B. Explain some of the variability of the dependent variable Y due to the relationship between Y and an independent variable X.
C. Compare the response variable Y and the predictor variable X.
D. Describe the dependence of the response variable Y on the predictor variable X.
A manufacturer claims that a particular automobile will get at least 50 miles per gallon on the highway. The researchers at a consumer-oriented magazine plans to test this claim with a simple random sample of 30 cars. Assuming that the standard deviation between individual cars is 2.3 miles per gallon, what should the researchers conclude if the sample mean is 49 miles per gallon?
A. There is not sufficient evidence to reject the manufacturer’s claim; 49 miles per gallon is too close to the claimed 50 miles per gallon.
B. The manufacturer’s claim should not be rejected because the p-value of 0.0086 is too small.
C. The manufacturer’s claim should be rejected because the sample mean is less than the claimed mean.
D. The p-value of 0.0086 is sufficient evidence to reject the manufacturer’s claim.
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