Regression Statistics Multiple R R Square Adjusted R Square 0.707 Standard Error Observations ANOVA SS ee 770.17 7 .17 MSb Significance F 17.92274 0.005478716 icublesR fetoT df Regression Residual 257.83 Total Standard e Upper 95% Suisy Coefficients SHEO 165.46 2000 -21.48 Error t Statoreo P-value Lower 95% Intercept 21.3860 5.07 O 0.000 ERA 0.005
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- For unemployed persons in the United States, the average number of months ofunemployment at the end of December 2009 was approximately seven months(Bureau of Labor Statistics, January 2010). Suppose the following data are for aparticular region in upstate New York. The values in the first column show thenumber of months unemployed and the values in the second column show thecorresponding number of unemployed persons.MonthsUnemployedNumberUnemployed1 10292 16863 22694 26755 34876 46527 41458 35879 2325 10 1120Let x be a random variable indicating the number of months a person is unemployed.a. Use the data to develop an empirical discrete probability distribution for x.b. Show that your probability distribution satisfies the conditions for a validdiscrete probability distribution.c. What is the probability that a person is unemployed for two months or less?Unemployed for more than two months?d. What is the probability that a person is unemployed for more than sixmonths?The following data has been collected on the interarrival times of patients to an emergency department: 3.772, 1.761, 0.743, 15.988, 0.412, 7.541, 6.900, 3.447, 7.024, 1.061, 5.449, 0.309, 0.766, 4.807, 8.143, 0.093, 9.524, 0.012, 4.634, and 0.195 minutes. Estimate the squared coefficient of variation of the arrival process. Is the arrival process likely to be Poisson? Why or why not? Estimate the arrival rate?A lecturer at WIN wanted to know if he can predict student’s quiz results by asking them tocomplete a simple survey. The result of the survey is found in the file: Assignment 2 sem22020data set 1. Quiz Results EQR Study Hrs Age Sex BBT MB MC AuHS LM 15 10 3 19 0 0 1 1 0 1 14 15 4 24 0 0 1 0 0 1 9 15 1 20 0 10 1 0 0 1 6 10 3 21 0 0 1 1 0 1 14 15 4 21 0 9 1 0 0 1 12 10 6 21 0 2 0 1 0 1 12 13 2 21 1 8 1 0 0 0 15 15 0 20 0 8 1 0 0 1 12 15 3 20 0 10 1 0 0 1 13 15 0.2 19 0 8 1 0 0 1 15 15 2 20 0 6 1 0 1 1 12 14 5 20 0 5 1 1 1 1 14 15 7 22 0 8 0 0 0 0 7 7 10 21 1 7 0 0 1 0 11 15 5 24 0 0 1 0 0 1 10 10 3 22 1 0 1 0 0 1 13 11 3 23 1 1 1 1 1 1 13 15 2 22 1 8 0 0 0 0 13 12 4 20 1 7 1 0 1 0 13 10 3 20 1 0 1 0 0 1 8 13 5 20 1 8 0 0 0 0 12 13 5 22 0 5 0 0 0 1 13 15 8 22 0 5 0 1 0 1 10 13 4 23 1 7 1 0 0 1 13 13 0.5 20 1 0 0 0 0 0 12 13 0.5 20 1 0 1 0 0 0 15 15 2 21 0 10 1 0 0 1 10 13 6 22 0 6 1 1 0 1 11 8 5 20 0 10 0 0 1 0 12 10 4 19 1…
- Is the number of square feet of living space a good predictor of a house’s selling price? The following data collected in April, 2015, show the square footage and selling price for fifteen houses in Winston Salem, North Carolina. Size (1000s sq. ft) Selling Price ($1000s) 1.26 117.5 3.02 299.9 1.99 139.0 0.91 45.6 1.87 129.9 2.63 274.9 2.60 259.9 2.27 177.0 2.30 175.0 2.08 189.9 1.12 95.0 1.38 82.1 1.80 169.0 1.57 96.5 1.45 114.9 Develop a scatter diagram with square feet of living space as the independent variable and selling price as the dependent variable. What does the scatter diagram indicate about the relationship between the size of a house and the selling price? a. Develop the estimated regression equation that could be used to predict the selling price given the number of square feet of living space. Please do not hand write. thank you.Kaitlyn measures the upload speed in megabits per second of her home broadband internet connection during peak hours and off-peak hours. The results are provided in the accompanying table. Peak Off-Peak 5.83 5.14 6.05 6.80 7.14 6.98 3.54 5.77 5.45 7.27 5.90 6.62 5.81 6.19 4.82 6.08 6.37 6.59 4.65 5.58 5.30 7.41 6.48 6.26 5.96 6.37 5.79 6.31 6.84 6.55 5.06 4.95 5.61 7.03 6.45 6.77 Examine the results of Kaitlyn's test to determine the statements that compare the medians and interquartile ranges of the data sets to each other in terms of this situation. Select the two correct answers. The median upload speed during peak hours is 5.905 megabits per second, which is less than the median upload speed during off-peak hours, 7.005 megabits per second. The upload speeds during peak hours are slower on average compared to off-peak times. The median upload speed during peak hours is 6.37 megabits per second, which is greater than the median upload speed during…An agent for a property management company would like to be able to predict the monthly rental cost for apartments based on the size of the apartment as defined by square footage. A sample of the rent of 25 apartments in a college rental neighborhood was selected, and the information collected revealed the following: Apartment Size (Sq. Ft.) Monthly Rent ($) 1 850 950 2 1,450 1,600 3 1,085 1,200 4 1,232 1,500 5 718 950 6 1,485 1,700 7 1,136 1,650 8 726 935 9 700 875 10 956 1,150 11 1,100 1,400 12 1,285 1,650 13 1,985 2,300 14 1,369 1,800 15 1,175 1,400 16 1,225 1,450 17 1,245 1,100 18 1,259 1,700 19 1,150 1,200 20 896 1,150 21 1,361 1,600 22 1,040 1,650 23 755 1,200 24 1,000 800 25 1,200 1,750 e) Determine the coefficient of determination r2 and then completely interpret…
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- You work for an insurance company and are studying the relationship between types of crashes and the vehicles involved. As part of your study, you randomly select 3632 vehicle crashes and organize the resulting data as shown in the contigency table. At α=0.01, can you conclude that the type of crash depends on the type of vehicle? Complete parts (a) through (d). Vehicle Type of crash Car Pickup Sport utility Single-vehicle 876 393 342 Multiple-vehicle 1143 475 403 Question content area bottom Part 1 (a) Identify the claim and state the null and alternative hypotheses. H0: The type of crash and the type of vehicle are . Ha: The type of crash and the type of vehicle are . (a) Identify the claim and state the null and alternative hypotheses. H0: The type of crash and the type of vehicle are Ha: The type of crash and the type of vehicle are . The alternative hypothesis is the claim. Part 2 (b) Determine the degrees of…An automobile dealer conducted a test to determine if the time in minutes needed to complete a minor engine tune-up depends on whether a computerized engine analyzer or an electronic analyzer is used. Because tune-up time varies among compact, intermediate, and full-sized cars, the three types of cars were used as blocks in the experiment. The data obtained follow. Analyzer Computerized Electronic Car Compact 51 42 Intermediate 55 43 Full-sized 62 47 Use ? = 0.05 to test for any significant differences. State the null and alternative hypotheses. H0: ?Computerized ≠ ?ElectronicHa: ?Computerized = ?ElectronicH0: ?Computerized = ?Electronic = ?Compact = ?Intermediate = ?Full-sizedHa: Not all the population means are equal. H0: ?Computerized = ?ElectronicHa: ?Computerized ≠ ?ElectronicH0: ?Compact ≠ ?Intermediate ≠ ?Full-sizedHa: ?Compact = ?Intermediate = ?Full-sizedH0: ?Compact = ?Intermediate = ?Full-sizedHa: ?Compact ≠ ?Intermediate ≠ ?Full-sized Find the value of…If a researcher wants to find out the average monthly expenses of all university students in Edmonton, this average would be an example of ________ . a. samplecross out b. statisticcross out c. populationcross out d. parameter