Answer - C-Manipulated by the experimentor.
A variable is defined as anything that has a quality or quantity that varies.
Variables are of many types. The main divisions of variables are
-Independent variables
-Dependent variables
Independent variables are those which can be manipulated by the experimentor.
Dependent variables are those which is dependent on the independent variable and can't be manipulated by the experimentor. It varies based on the independent variable.
An independent variable is A Used on in surveys B) Separate from the correlation C Manipulated...
2. Let the following data be given where X is the independent variable and Y is the dependent variable Find the correlation coefficient r a. a and B,onpfrom the sample for the model: b. Estimate +tx and the actual data Y where ε is the random error between the fitted model f by Y write the linear equation P=" dr-h Predict the value of P when x = 8 c. d. 2. Let the following data be given where X...
Which of the following is true? A.The predictive power of an independent variable comes from the level of correlation that it has with the dependent variable. B. If you have a variable with several categories like days of the week, there is no way that you can convert the categories to a quantitative variable. C. All of the answers on this list are true. If the p-value for an independent variable is lower than 0.05, then we should discard that...
Cost-Volume-Profit Relations: Missing Data Following are data from 4 separate companies. Supply the missing data in each independent case.Case ACase BCase CCase DUnit Sales1,000800Sales revenue$20,000$$60000Variable cost per unit$10$1$12$Contribution margin$$800$$Fixed Costs$7,000$$80,000$Net income$$500$$Unit contribution margin$$$$15Break-even point (units)4,0002,000Margin of safety (units)3001,000
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Regression and Multicollinearity When multiple independent variables are used to predict a dependent variable in multiple regression, multicollinearity among the independent variables is often a concern. What is the main problem caused by high multicollinearity among the independent variables in a multiple regression equation? Can you still achieve a high r for your regression equation if multicollinearity is present in your data? Regression and Multicollinearity When multiple independent variables are used to predict a dependent variable in multiple regression, multicollinearity...
1. Match the correlation coefficient to its variable. Population Correlation (choose below) a. c b. p (Greek rho) c. r d.R c. Greek alpha Sample Correlation (choose below) a. c b. p (Greek rho) c. r d.R c. Greek alpha Question 7 1 pts Which of the correlation values represent a perfect linear relationship between x and y? 0-1 O1 0.05 100