CWP Test Questions With 100% Correct Answers Latest Updated | Graded A+

CWP Test Questions With 100% Correct Answers Latest Updated | Graded A+. I am using x to predict y. When I know the value of x, the mean-squared-error of my estimate of y is less than when I don't know x. - answer-x explains some of the variance in y If the SSmodel is greater than the SSresidual... - answer-the model accounts for more than 50% of the total variance What is the coefficient of determination? - answer-The proportion of variance accounted for in the dependent variable by the predictor variables. What is the relationship between r and beta in a simple regression? - answer-beta is an unstandardised measure of r What is the critical value for t with 5 degrees of freedom and an alpha of 0.05 twotailed? Give your answer to 2 decimal places. - answer-2.57 You have the following data: x = c(10,3,2,1,3,4,5,6) y = c(2,14,18,12,10,11,8,9) You run a linear model and get the following estimate of the slope: ^B1 = -1.423 What is the standardised beta? Report to 2 decimal place - answer--0.86 If I have a lot of error in my regression model, it means that: - answer-There are big differences between the line specified by my model and the corresponding points on the scatterplot. If the beta for your x term in a regression model is negative, it means: - answer-That there as x increases, y decreases. I conduct a study to investigate whether average hours of sleep per nigh (x) predicts sick days per year (y). I find the follow values for the intercept and slope: B0 = 25 B1 = -1.6 CWP Test Questions With 100% Correct Answers Latest Updated 2024- 2025 | Graded A+ True or false, the following is the correct interpretation of the intercept: A person who sleeps 0 hours on average per night is expected to have 24 sick days per year. - answer-False I conduct a study to investigate whether average hours of sleep per nigh (x) predicts sick days per year (y). I find the follow values for the intercept and slope: B0 = 25 B1 = -1.6 True or false, the following is the correct interpretation of the slope: For every hour of sleep a person has on average per night, the number of sick days per year decreases by 1.6 days. - answer-True What is the critical value for t with 5 degrees of freedom and an alpha of 0.01 twotailed? Give your answer to 2 decimal places in the form X.XX - answer-4.03 You run a linear model with a single binary predictor. The intercept for the model is 110, and the unstandardized beta is 17.1. What is the mean of the group coded 1? - answer-127.1 You run a linear model with a single binary predictor (0 = Group0; 1 = Group1). The mean of Group1 is 75 and the beta coefficient is 7. What is the value of the intercept? - answer-68 If regression model errors (residuals), show different amounts of variation across the range of measurement, they are referred to as ... - answer-Heteroscedastic Match the assumption/diagnostic to the most appropriate test. Shapiro-Wilk Test - answer-Normality of residuals Match the assumption/diagnostic to the most appropriate test. Durbin-Watson Test - answer-Autocorrelation of residuals Match the assumption/diagnostic to the most appropriate test. Non-constant variance test - answer-Heteroscedasticity Match the assumption/diagnostic to the most appropriate visualization. Histogram - answer-Normality of residuals Match the assumption/diagnostic to the most appropriate visualization. Scatterplot - answer-Linearity Match the assumption/diagnostic to the most appropriate visualization. Residual-vs-predicted plot - answer-Heteroscedasticity The null hypothesis for the non-constant variance test (Breusch-Pagan test) is that the data are heteroscedastic. True or False? - answer-False What are the degrees of freedom for the sums of squares total in a linear model? - answer-n-1 Which R function can be used to calculate from a model object? - answer-predict() In a simple linear model where both variables are continuous and z-scored, what is the value of the intercept? - answer-0 The null hypothesis for the non-constant variance test (Breusch-Pagan test) is that the data are heteroscedastic. True or false? - answer-False In testing model assumptions and appropriateness, what quantities summarise the influence of an individual case on the predicted values for that same case? - answerCook's distance Given the following: hat y = 10.5 + 4.3*x What is the predicted score for someone scoring 7 for x? Give you answer to two decimal places in the form X.XX - answer-40.60 Assuming we have a data set called df, that contains variables called DV and IV, the following R code will run without error? lm(DV ~ IV data = df) True or false? - answer-False In multiple regression high leverage values would have... - answer-X values far from the centroid of X Suppose we have a study with: Sample size (n) = 73 Number of predictors (k) = 11 Which of the following would be considered high influence cases based on Di 4/(nk-1) ? - answer-Cook's distance = 0.09 What is the critical value for F with 5,58 degrees of freedom and an alpha of 0.05? Give your answer to 2 decimal places in the form X.XX - answer-2.37 Given the following linear model equation: y = 10 + 6x(1) + 2x(2) + 3x(3) What would the predicted score for Y be for an individual with the following scores: x1 = 2 x2 = 6 x3 = 0 - answer-34 I have a categorical variable (`condition`) with 4 levels and the following group means: Control = 32 Group 1 = 23 Group 2 = 10 Group 3 = 5 I use this variable to predict an outcome variable (`test_score`). The two variables are in a data frame called `df`. I run the following code in R: contrasts(df$condition) - ment(4, based = 2) lm(test_score ~ condition, data = df) What will b3 equal in this model? Report your answer in the form X.XX - answer--18 (The code uses dummy codes, but sets Group 1 as the reference group. b3 will code for the third comparison, which will be the difference between Group 3 and Group 1. (Group 3 - Group 1 = 5 - 23 = -18.00)) I have the following linear model equation: y = 10 + 6x(1) + 2x(2) + 3x(3) What does the beta of x1 mean? - answer-That a one unit change in x1 produces a six unit change in y when all other variables are held constant. All else being equal, which of these will increase the predictive power of your linear model? - answer-Increasing the variance in (one of) your predictor(s) I have a categorical predictor with 7 levels. How many dummy coded variables are required in a linear model to fully represent the variable? - answer-6 Highly correlated predictors make the standard error of the coefficients smaller. True or false? - answer-False, correlated predictors make us less certain about the effect of a single variable, and thus make the SE larger. I run the following linear model: DV = b0 + b1x1 + b2x2 + b3x3 +b4x4 + e In a sample of 200 participants. I have an r-squared value of 0.27. What is my adjusted r-square? Report to 2 decimal places in the form X.XX - answer-0.26 (Formula: 1 - (1-Rsquared) x [(N-1)/N-k-1] What are the two features of a model which form part of the adjusted r-square calculation? - answer-Sample size and number of predictors The mean square model is calculated by: - answer-Dividing the sum of squares for the model by k, where k is the number of predictors. Mean squares calculations divide sums of squares by the associated degrees of freedom. Degrees of freedom connected to models will be focused on the number of predictors.