Question 3: The relationship between the number of years of experience and salary for accountants in California is being studied. A sample of fourteen accountants were observed and the data recorded. The following scatterplot and regression analysis resulted: 90000 80000 n = 14 2 70000 ý = 58,111.29 + 2511.25x %3D
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Given a scatterplot that shows the relationship between numbers of years of experience and salary
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- ) Professor Piraneo has three classes with 80 students total. He created a distribution for mid-term scores as follows Score No. of students 90 -100 12 80 -89 30 70 -79 14 60 -69 16 0 -59 8 Suppose that a student of Professor Piraneo is selected at random. Let F= the event the student scores under 60 G= the event the student scored in the 60s Have the answer of these H= the event the student scored in the 70s I= the event the student scored under 80 a) Use the table and the f/N rule to find P(I) b) Express the event I in terms of F, G, and H c) Determine P(F), P(G), and P(H) d) Compute P(I), using the special addition rule and your answers from parts (b) and (c). Compare…Hello. How do you calculate this question on a TI-83? Thanks.Consider the following passage: I ran a regression, with many variables to predict the result of another variable which was the murder rate. One can see that lots of things, can cause the murder rate to increase or decrease. I tried to account for all the important factors, and those factors are the SAT scores, unemployment rate, and international migration per 1,000. The SAT score is, average combined total score participants did on the SAT exam. The unemployment rate is, "a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force." (Wikipedia) International migration per 1,000 is, the number of people who come into a state from other countries per 1,000 people who live in the state. After I run the regression I will look at the t scores and p values and I should hopefully conclude that international migration does not cause crime. Which writing mistakes, if any, did…
- Which of the following statements is sensible? A 102.4% of the total variation in a football player's weight is accounted for, or explained by its linear regression with the time spent practicing football. B. The correlation coefficient between a car's length and its fuel efficiency is7 es per gallon. C. There is a very strong direct linear correlation (0.95) between amount of d od consumption and the brand of dog food. D. The correlation coefficient between the amounts of fertilizer used and quantity of beans harvested is 0.42. OD O A OBFor each of the following data sets: plot the data, determine the regression equation, and add the graph of the regression to the graph.Body Fat. Where we considered the regression of percentage of body fat on nine body measurements: height, weight, hip, forearm, neck, wrist, triceps, scapula, and sup. Describe and discuss problems that could have arisen in the collection of the data for this regression analysis.
- The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor's degree in business administration. GPA 2.6 3.4 3.6 3.2 3.5 2.9 Monthly Salary ($) 3,500 3,900 4,200 3,800 4,200 3,900 The estimated regression equation for these data is ý = 1,970.72 + 608.11x and MSE = 18,671.17. (a) Develop a point estimate of the starting salary (in dollars) for a student with a GPA of 3.1. (Round your answer to the nearest cent). (b) Develop a 95% confidence interval for the mean starting salary (in dollars) for all students with a 3.1 GPA. (Round your answers to the nearest cent). to $ (c) Develop a 95% prediction interval (in dollars) for Ryan Dailey, a student with a GPA of 3.1. (Round your answers to the nearest cent). to $Hiroshi Sato, an owner of a sushi restaurant in San Francisco, has been following an aggressive marketing campaign to thwart the effect of rising unemployment rates on business. He used monthly data on sales ($1,000s), advertising costs ($), and the unemployment rate (%) fromJanuary 2008 to May 2009 to estimate the following sample regression equation: Sales(t) = 17.51 +0.05 Advertising Costs(t-1) – 0.70 Unemployment Rate t-1 Requirement: a. Hiroshi had budgeted $620 toward advertising costs in May 2009. Make a forecast in June2009, if the unemployment rate in May 2009 was 9.1%b. What will be the forecast if he raises his advertisement budget to $700?c. Reevaluate the above forecast if the unemployment rate in May 2009 was 9.5%. Please, if possible, can you do the answer in Excel/SpreadsheetThe following data are the monthly salaries and the grade point averages for students who obtained a bachelor's degree in mathematics. GPA: 2.6, 3.4, 3.6, 3.2, 3.5, and 2.9; Monthly Salary: 330o, 3600, 4000, 3500, 3900, and 3600. Plot the scatter diagram showing the deviations about the estimated regression line and the line y = y(bar).
- For the following example indicate the type of data involved using the following: A = nominal data B = ordinal data C = interval data 1. Number of patients with coronary pathology in nursing homes in the U.SThe EPA records data on the fuel economy of many different makes of cars. They are interested in determining if one could predict the mileage of the car (in miles per gallon) from the weight of the car (in pounds). What is the response variable to this study?Consider the following passage: I ran a regression, with many variables to predict the result of another variable which was the murder rate. One can see that lots of things, can cause the murder rate to increase or decrease. I tried to account for all the important factors, and those factors are the SAT scores, unemployment rate, and international migration per 1,000. The SAT score is, average combined total score participants did on the SAT exam. The unemployment rate is, "a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force." (Wikipedia) International migration per 1,000 is, the number of people who come into a state from other countries per 1,000 people who live in the state. After I run the regression I will look at the t scores and p values and I should hopefully conclude that international migration does not cause crime. Which writing mistakes, if any, did…