2. (9 points) Name one or more graphs that can be used to validate each of...
(4 points) Residuals vs fitted plots can be used to assess whether the four key assumptions for a simple linear regression have been met. Each of the plots below displays an instance where at least one of these assumptions may not have been met. For each plot, identify which assumption has been most violated, if any. 1. Plot A shows that A. The relationship between x and y cannot be assumed to be linear. B. The residuals do not appear...
Which of the following are assumptions for the linear regression model? CHECK THAT ALL MAY APPLY!!! Select one or more: a. Regression function (i.e., equation) is linear. b. Error terms are normally distributed. c. Error terms are independent. d. Error terms have constant variance. e. Regression model fits all observations (i.e., no outliers).
Heteroscedasticity, in the context of regression, a. leads to more accurate estimates of the standard deviations of the estimated parameters than when homoscedasticity is present. b. occurs when the X variables are correlated with one another. c. can be corrected by removing all X variables from the model. d. occurs when the error terms, εi, do not have constant variance for all values of the predictor (or X) variables. e. is an assumption of the Gauss-Markov theorem.
1. A researcher has just finished a statistical analysis and claims that he found evidence that x affects y positively. Using a 1-tailed test, he found that the estimated coefficient for x is significantly positive at the 5% level, but is not significant at the 4% level. Assume that the classical linear regression assumptions hold. If the researcher used a 2-tailed test instead, what would he have found? a. The estimated coefficient for x is significantly positive at the 2.5%...
4 13 points consider this ANOVA table that was produced from by a simple linear regression model to a dataset. While this is based on a real dataset, for the purposes of this pro will only describe the variables as the response variable (Y) and the explanatory van Analysis of Variance Source DF SS MS F P Regression 1 793.28 793.281 40.35 0.000 25 491.53 19.661 26 1284.81 Error Total n were NOT checked prior to producing this The assumption...
Below are four bivariate data sets and the scatter plot for each. (Note that each scatter plot is displayed on the same scale.) Each data set is made up of sample values drawn from a population. 2.0 3.0 3.0 3.0 mo Figure 1.0 7.5 : 201 9.2 3.0 6.9 4. 05. 5. 0 8 .2 EAN Hool 6.0 46 1 7.8 9. 0 6 .2 20.0145 Figure Answer the following questions. The same response may be the correct answer for...
need help on number 25
23) For a one-way ANOVA, the F statistic represents e) f) a and e a and d Questions 24-26 refer to the follawing dota problem. Values of X and Y are provided. space in the table for any necessory calculations Use the additional 1.8 3.0 4.2 6.0 3.0 4.0 2.4 5.0 6.3 24) What is the slope of the relationship between X and 7.96 a) 06538 b) 0.6352 c) 0.0612 e) 0.6210 25) What is...
When are bar graphs typically used, as apposed to something else, like a scatter plot? Choose all that apply. when there are multiple groups to look at when you publish you always have to make bar graphs when there is just one group to look at only when you have a monotonic relationship between your groups when you want to graphically display the effects between groups with error bars so that you can get a quick visualization of your data...
Pass Task3. Read the following narrative: Jims Gyms have a number of fitness clubs. Each club has a name, establishment date, and a description. Clients (who have an ID and name) can join one or more of these fitness clubs. As a client joins a club, the date that the client joined is to be recorded Draw an ERD based on this information. Expand all M:M relationships. Do not introduce any surrogate keys. The ERD may be neatly hand drawn...
The correlation coefficients can be used to measure Select one: O a. The relationship of two independent variables to each other. O b. The relationship of two related variables to each other. O C. The relationship between two dependent variables to each other. d. All of the above.