Determine if the following statements is true or false. If it is true, write TRUE. If it is false, change the underlined word to make the statement true and write the correct word(s) as your answer.( 1. The point estimator is unbiased. Thus, the bias is equal to one. 2. If two competing estimators are both unbiased, the one with the smaller variance is said to be relatively more efficient. 3. A prediction interval covers a specified proportion of the population for a given confidence level. 4. The null hypothesis must always contain an equality. 5. The statement "There is no statistical significance between the length of lecture hours to exam performance." is an example of a/an alternative hypothesis. 6. The probability of rejecting the null hypothesis when in fact it is true is known as the level of confidence. 7. If we accept a null hypothesis that must be rejected, then we are committing a Type 2 error. 8. Ap-value of 0.02 indicates that you have only 20% chance of drawing the sample tested if the null hypothesis was actually true. 3. The one sample t-test the mean of a single group against a known population. 10. The paired sample t-test compares the mean for two groups of sample. 11. In the simple linear regression model: Y, = Bo+ B,X, + 81, Ba is the y intercept of the regression line. 12. The correlation coefficient measures the strength of the linear relationship between the response variable and the set of explanatory variable. 3. The coefficient of correlation is the proportion of variation in the response variable explained by the regression model. 4. A correlation coefficient from 0.9 to 1.00 means a very high positive correlation. 5. The line of best fit through data points always represents a linear relationship between the independent and dependent variable.

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Determine if the following statements is true or false. If it is true, write TRUE, If it is false, change the underlined word to
make the statement true and write the correct word(s) as your answer.(
1. The point estimator is unbiased. Thus, the bias is equal to one.
2. If two competing estimators are both unbiased, the one with the smaller variance is said to be relatively more efficient.
3. A prediction interval covers a specified proportion of the population for a given confidence level.
4. The null hypothesis must always contain an equality.
5. The statement "There is no statistical significance between the length of lecture hours to exam performance." is an
example of a/an alternative hypothesis.
6. The probability of rejecting the null hypothesis when in fact it is true is known as the level of confidence.
7. If we accept a null hypothesis that must be rejected, then we are committing a Type 2 error.
8. Ap-value of 0.02 indicates that you have only 20% chance of drawing the sample tested if the null hypothesis was
actually true.
9. The one sample t-test the mean of a single group against a known population.
10. The paired sample t-test compares the mean for two groups of sample.
11. In the simple linear regression model: Y, = Bo + B1X¢ + E, ß1 is the y intercept of the regression line.
12. The correlation coefficient measures the strength of the linear relationship between the response variable and the set of
explanatory variable.
13. The coefficient of correlation is the proportion of variation in the response variable explained by the regression model.
14. A correlation coefficient from 0.9 to 1.00 means a very high positive correlation.
15. The line of best fit through data points always represents a linear relationship between the independent and dependent
variable.
Transcribed Image Text:Determine if the following statements is true or false. If it is true, write TRUE, If it is false, change the underlined word to make the statement true and write the correct word(s) as your answer.( 1. The point estimator is unbiased. Thus, the bias is equal to one. 2. If two competing estimators are both unbiased, the one with the smaller variance is said to be relatively more efficient. 3. A prediction interval covers a specified proportion of the population for a given confidence level. 4. The null hypothesis must always contain an equality. 5. The statement "There is no statistical significance between the length of lecture hours to exam performance." is an example of a/an alternative hypothesis. 6. The probability of rejecting the null hypothesis when in fact it is true is known as the level of confidence. 7. If we accept a null hypothesis that must be rejected, then we are committing a Type 2 error. 8. Ap-value of 0.02 indicates that you have only 20% chance of drawing the sample tested if the null hypothesis was actually true. 9. The one sample t-test the mean of a single group against a known population. 10. The paired sample t-test compares the mean for two groups of sample. 11. In the simple linear regression model: Y, = Bo + B1X¢ + E, ß1 is the y intercept of the regression line. 12. The correlation coefficient measures the strength of the linear relationship between the response variable and the set of explanatory variable. 13. The coefficient of correlation is the proportion of variation in the response variable explained by the regression model. 14. A correlation coefficient from 0.9 to 1.00 means a very high positive correlation. 15. The line of best fit through data points always represents a linear relationship between the independent and dependent variable.
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