If one gets a very small p value for a correlation between two variables, does it indicate a strong relationship between the two variables?
If one gets a very small p value for a correlation between two variables, does it indicate a strong relationship between the two variables?
The data shown in the following scatterplot show a very nice relationship between the two variables. However, the correlation here is 0.03, very close to zero. Explain why we can have a nice relationship between two quantitative variables and yet have a correlation of O 8 10 14 O There are no outliers but there are influential observations that cause the value of r to be near 0. 0 There are strong outliers that cause the value of to be...
What does a correlation coefficient of 0 indicate? Choose the correct answer below. O A. There is no linear relationship between the two quantitative variables. O B. There is a weak relationship between the two quantitative variables. O C. It indicates a calculation error, as the correlation coefficient cannot be 0. O D. There is a strong relationship between the two quantitative variables. O E. It indicates a non-linear relationship between the two quantitative variables.
QUESTION 6 Suppose the correlation coefficient between two variables is found to be -0.94. Which of the following statements are true? there is a strong tendency for small values of one variable to be associated with large values of the other variable there is a weak negative relationship between the variables a scatter plot of the data points would show a clear downward trend there is a strong tendency for low values of one variable to be paired with low...
Consider a two-dimensional scatterplot representing the relationship between two continuous variables. If the correlation coefficient is -1, then: a. All points lie in a straight line with a slope of -1. b. All points lie in a straight line with an unknown negative slope. c. All points do not lie in a straight line but the best fitting regression line has a slope of -1. d. There is a strong positive relationship between the two variables.
1. construct a scatter plot for the variables 2. compute the value of the correlation coefficient 3. give an explanation of the type nof relationship that exists between the two variables. The explanation should be a short paragraph. In this paragraph inclue the following: *say whether the is a strong positiv elinear correlation, weak positive linear correlation, strong ngative linear correlation, weak negative correlation, or no linear correlation between the two variables. *explain how you can see this from the...
Assess whether the following correlation coefficients denote a very strong relationship, strong relationship, moderate relationship, weak relationship, or no relationship at all: a) -0.74 b) -0.12 c) +0.28 d) -0.93 e) +0.84 f) Now place these correlation coefficients in order from weakest to strongest relationship.
MTQ 6- A coefficient of correlation is computed to be -2.0. It means that The relationship between two variables is weak. The relationship between two variables is strong and positive The relationship between two variables is strong and negative Correlation coefficient cannot have this value 7- Which one of the following is not unbiased estimators Sample Proportions Sample Means Sample Variances Sample Medians
Describe in words the nature of the relationship between each pair of variables. Give a verbal description of the way the variables are related (how are changes in one variable related to changes in the other). This should include the direction of the relationship (what does it mean if the correlation value is positive or negative) and the strength of the relationship (is there a strong or weak correlation). r = -.82 between a job applicant's age and likelihood of...
A correlation coefficient is computed to be -0.95 means that the relationship between two variables is weak because it is negative. True/False
In the effort to understand a relationship between two variables, correlation is an improvement over covariance, and simple regression is an improvement over correlation. Write a essay in which you explain covariance, correlation, and simple regression and why each would be preferred over the one before it. Use an imagined high school class as the target audience of your explanation.