When we test the hypothesis for a significant correlation, we use which of the following statistics?
a. r
b. r squared
c. the regression equation
d. t
When we test the hypothesis for a significant correlation, we use which of the following statistics?...
Which of the following is the null hypothesis when you use the correlation coefficient? a. rho = 0 b. there is a relationship between the two variables c. there is not a null hypothesis when you test the significance of r. d. The correlation will not be negative
Use the given information to complete the test to determine if there is significant linear correlation between numbers of hours a student spent preparing for a test and test scores. Use a significance level of 0.05. 1) The test scores of 6 randomly picked students and the numbers of hours they prepared are 1) as follows: Hours 5 10 4 6 10 9 Score 64 86 69 86 59 87 The equation of the regression line is y = 1.06604x...
1. When testing joint hypothesis, you should a. use t-statistics for each single hypothesis in H0 and reject the H0 if all of the restrictions fail. b. use the F-statistic and reject all the hypotheses in H0 if the statistic exceeds the critical value. c. use t-statistics for each single hypothesis and reject the H0 once the statistic exceeds the critical value for a single hypothesis. d. use the F-statistics and reject at least one of the hypotheses in H0...
When we conclude that β1 = 0 in a test of hypothesis or a test for significance of regression, we can also conclude that the correlation, ρ, is equal to ______
In determining if this regression is significant, I observed the
following, am I taking the correct approach?
To check if your results are reliable (statistically
significant), look at Significance F (0.00). If this value is less
than 0.05, the regression is acceptable. If Significance F is
greater than 0.05, it's advisable to stop using this set of
independent variables.
As part of the hypothesis test, we should evaluate R-squared as
it measures the strength of the relationship between the model...
1. When do we use an independent groups t-test? a. b. c. d. When we are comparing means from one sample that has been measured twice. When we are comparing means from two different samples. When we are comparing a sample mean to a population mean. When we are comparing two population means. 2. Which of the following is true regarding the use of t-tests for true experiments versus quasi-experimental designs? a. b. We use the same t-test whether it...
Indictator(s) that multicollinearity might be a problem are: A. The regression has statistically significant t statistics on the slope coefficients and the F statistic is not significant. B. The R-squared value is low in a regression of one Xj on the other regressors. C. The coefficients on the independent variables have the wrong signs. D. None of these issue indicate a potential problem with multicollinearity.
Suppose the following statistics are generated by a simple linear regression model. Which of these indicates that the regression model is statistically significant? If none of these then select “none”. a) Adjusted R squared = 0.0014 b) p = 0.001 c)none of these
Use EXCEL and screenshot all steps The following 6 questions are related. A statistics practitioner in an international company is investigating the factors that affect salary of sale managers. He wondered if evaluations by customers are related to salaries. To this end, he collected 100 observations on: y = Annual salary (in dollars) x = Mean score on customer evaluations To accomplish his goal, he assumes the following relationship: y = β(0) + β(1)x + ε Then, using...
for the data below test weather the linear correlation between x and y is significant. use a significance level of 0.05. X= 6, 8, 20, 28,36 Y= 2, 4, 13, 20, 30 null hypothesis alternative null= test statistics p value= reject or fail to reject null = formal conclusion=