The regression equation for predicting number of speeding tickets (Y) from information about driver age (X) is Y= -0.65(X) + 5.57. How many tickets would you predict for a twenty-year-old?
Also read:
- The regression equation for predicting number of speeding tickets (Y)
- Question: Q: Chapter Chapter 11 of Mertler and Vannata; answer exercises on pages 306 and 307: This exercise utilizes the SPSS data setprofile-e.sav, which can be downloaded from this Web site: www.Pvrczak.com/data Conduct a Forward: LR logistic regression analysis with the following variables: IV—age, educ, hrsl, sibs, rincom91, life2 (categorical) DV—satjob2 Note: The variable Iife2 is categorical such that dull = 1, routine/exciting = 2, and all other values are system missing. Develop a research question for the following scenario. Conduct a preliminary Linear Regression to identify outliers and evaluate multicollinearity among the five continuous variables . Complete the following: a. Using the Chi-Square table in Appendix B, identify the critical value atp< .001 for identifying outliers. Use Explore to determine if there are outliers. Which cases should be eliminated? b. Is multicollinearity a problem among the five continuous variables? Conduct Binary Logistic Regression using the Forward: LR method. IV—age, educ, hrsl, sibs, rincom91, life2 (categorical; last is the reference category) DV—satjob2 Note: Make sure that any outliers identified in Exercise 2a are removed from data before running the logistic regression. Also, designating life2 as a categorical covariate with the last category as the reference, essentially makes "routine/exciting" = 0 and "dull" = 1, so interpret the results accordingly. a. Which variables were entered into the model? b. To what degree does the model fit the data? Explain. c. Is the generated model significantly different from the constant-only model? d. How accurate is the model in predicting job satisfaction? e. What are the odds ratios for the model variables? Explain. Module 14 – Multi-level linear analyses: When do you use multi-level linear analyzes? Chapter 8 of Cronk (chapter below I wasn’t sure what was being asked) and answer all practice exercises; post your results here:
- Biddle and Hamermesh (1990) built a multiple regression model to study the tradeoff between time spent in sleeping and working and to look at other factors affecting sleep: Sleep = β0 + β1 totwrk + β2 educ + β3 age + ε where sleep and totwrk (total work) are measured in minutes per week and educ and age are measured in years. Suppose the following equation is estimated: Sleep = 3500 – 0.15 totwrk – 11.20 educ + 2.29 age + ε Discuss what would happen to someone’s sleep if they choose to work more. Analyze whether the factors of totwrk, educ, and age are enough factors to explain the variation in sleep. Explain which additional factors should be explored in order to explain the variation in sleep. Provide your reasoning.
- Disturbed by speeding cars outside his workplace, Nobel laureate Arthur Holly Compton designed a speed bump
- Kirkland Theater sells season tickets for six events
- A random sample of 100 students attending a concert spent an average of $142 on their tickets with a standard deviation of $47.50
- Need these 2 questions answered. 150 words total 75 for each question. Files are attached. Need referenced if using other source materials including chapter pages and appendix table. Thank you Question 1) Keri is the owner of a new restaurant in the downtown area of her hometown. To continuously improve service, she would like to know if completed dishes are being delivered to the customer’s table within one minute of being completed by the chef. A random sample of 75 completed dishes showed that 60 were delivered within one minute of completion. Calculate the 90%, 95%, and 99% confidence interval for the true population proportion. Interpret your response within the context of the situation. Refer to Chapter 17, pp. 427-430 on calculating confidence intervals. Click here for Table A.2 from the appendix. Your response should be at least 75 words in length, unless otherwise specified. You are required to use at least your textbook as source material for your response. All sources used, including the textbook, must be referenced; paraphrased and quoted material must have accompanying citations. Question 2) A random sample of 100 students attending a concert spent an average of $142 on their tickets with a standard deviation of $47.50. Calculate the 90%, 95%, and 99% confidence intervals for the mean amount of money spent by all students attending the concert. Interpret your response within the context of the situation. Refer to Chapter 17, pp. 427-430 on calculating confidence intervals. Click here for Table A.2 from the appendix. Your response should be at least 75 words in length, unless otherwise specified. You are required to use at least your textbook as source material for your response. All sources used, including the textbook, must be referenced; paraphrased and quoted material must have accompanying citations.
- determine the importance of predicting the pricing strategies of rival firms in an industry characterized by mutual interdependence