1. A q-q plot tells you how close to a normal distribution your data are T/F?
2. The adjusted r-squared is usually more accurate T/F?
3. If you want a better model, what statistic should you use to decide if one if better? __________
4. Outliers should be analyzed separately if we do not include them in our analysis T/F?
5. Correlation is not part of a regression equation T/F?
1. A q-q plot tells you how close to a normal distribution your data are T/F?...
1. A q-q plot tells you how close to a normal distribution your data are T/F? 2. The adjusted r-squared is usually more accurate T/F? 3. If you want a better model, what statistic should you use to decide if one if better? __________ 4. Outliers should be analyzed separately if we do not include them in our analysis T/F? 5. Correlation is not part of a regression equation T/F?
only part II is needed Regardless of your answer to (a), you come up with the following multiple regression model. b. Coefficients: Estimate Std. Error t value Pr>lt (Intercept) 72.2285 1.2697 56.89 2e-16 X2 X3 Residual standard error: 7.25 on 191 degrees of freedom Multiple R-squared: 0.494, Adjusted R-squared: 0.489 F-statistic: 93.3 on 2 and 191 DF, p-value: <2e-16 0.4590 0.0524-8.76 1.1e-15 0.4146 0.1290 3.21 0.0015** I) What percentage of the total variation in Life Expectancy can you explain with...
Question 5 (1 point) ✓ Saved Suppose you want to know whether travel experiences are related to knowledge of geography. You give a 15 item quiz on American Geography and you also ask how many states participants have visited then look to see if there is a relation between the 2 t-test O correlation Multiple Regression chi squared ANOVA (F test) Question 6 (1 point) ✓ Saved In an experiment designed to study the effects of exposure to an aggressive...
R is a little difficult for me, please answer if you can interpret the R code, I want to learn better how to interpret the R code 4. each 2 pts] Below is the R output for a simple linear regression model Coefficients: Estimate Std. Error t value Pr(>t) (Intercept) 77.863 4.199 18.544 3.54e-13 3.485 3.386 0.00329* 11.801 Signif. codes: 0 0.0010.010.05 0.11 Residual standard error: 3.597 on 18 degrees of freedom Multiple R-squared: 0.3891, Adjusted R-squared: 0.3552 F-statistic: 11.47...
(a) The following is taken from the output generated by an Excel analysis of expenditure data using multiple regression: Regression Statistics Multiple R 0.9280 0.8611 0.8365 Adjusted R2 Standard Error.1488 Observations21 ANOVA Source Regression Residual Total df MS Significance of F 1.66E-07 3 308.68 35.117 102.893 2.930 17 20 358.49 49.81 Coefficient Standard Error 6.2000 0.7260 0.7260 0.9500 t Stat 3.7097 0.2755 -2.0523 0.5158 23.00 0.20 Intercept X2 X3 0.49 (i) Find the limits of the 95 percent confidence interval...
Q) The CO2 dataset in R has data on plants from Quebec and Mississippi (denoted by the variable name ‘Type’) that were subjected to two different treatments (denoted by the variable name “Treatment”), chilled or nonchilled. I ran two regression models to see what variables best describe CO2 uptake of plants, given different conditions, with the output below: What are the regression equations for models 1 and 2? What kind of variable is “Treatment”? What does the sign of the...
1) You are reviewing a ridge regression model that your business partner is building. In the model, he has applied the shrinkage penalty to all terms (intercept included), leading to a massive reduction in variance. Is everything okay with this implementation? (Choose the MOST CORRECT answer.) a) Yes, the ridge regression model is implemented properly. b) No, there should be a massive reduction in bias (not variance). c) No, the shrinkage penalty term does not apply to the intercept. d)...
PLEASE ANSWER ALL parts . IF YOU CANT ANSWER ALL, KINDLY ANSWER PART (E) AND PART(F) FOR PART (E) THE REGRESSION MODEL IS ALSO GIVE AT THE END. REGRESSION MODEL: We will be returning to the mtcars dataset, last seen in assignment 4. The dataset mtcars is built into R. It was extracted from the 1974 Motor Trend US magazine, and comcaprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models). You can find...
Question 1 You are interested in studying the effect of the US minimum Rico. Therefore you use the following dataset wage on employment in Puerto Variable LPREPOP Log of the Puerto Rican employment per capita LMINCOVLog of the minimum wage relative to average wages Description time trend (1 to 38) LUSGNP Log of US gross national product a) Explain what autocorrelation is. Provide an example which illustrates the regression problem, and describe a method that can be used to reduce...
True (T) or False (F) - 5 points (NO NEED TO EXPLAIN, JUST SAY WHETHER IT IS TRUE OR FALSE) B. 1. R-squared never decreases when you add more regressors. In panel data we can observe many individuals across more than one point in time. 2. 3. We want to test the effect of a speed limit change in New Mexico. When choosing a control state, we should try to find a state that also had a change in speed...