Practice ExerciseClassify the following random variables as discrete or continuous.1. The number of defective computers produced by a manufacturer2. The weight of newborns each year in a hospital3. The number of siblings in a family of a region4. The amount of paint utilized in a building project5. The number of dropouts in a school district for a period of 10 years6. The speed of a car7. The number of female athletes8. The time needed to finish the test9. The amount of sugar in a cup of coffee10. The number of people who are playing LOTTO each day

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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1. Tim Hortons wanted to estimate the difference in the mean amounts of caffeine in two brands of coffee. They took a sample of 18-lbs jars of Brand I and another sample of 13-lbs jars of Brand II coffee. The following summary data (sample statistics) are collected? nį = 10 x, = 23 S1 = 3 Brand I Brand II n2 = 12 x2 = 25 S2 = 4 Assume that the two populations are normally distributed. A. Test at 5 % level of significance, whether there is a difference in the mean amounts of caffeine between the 2 brands of coffee. B. Construct a 95% Confidence Interval to estimate the difference in the mean amounts of caffeine in 2 brands of coffee. C. Does the result in part b) confirm your findings from part a)?
A time analyst for the Super-Fast speedway pit crew observed the mechanic in charge of changing both front tires during a pit-stop practice session. The mechanic’s job is divided into six work elements and a preparation time between drills. The element times (in seconds) for the first six cycles are shown in Table.a. Calculate the normal time for changing tires.b. What sample size is appropriate for estimating the average time for work element 3 within +-1 percent of the true mean with 99 percent confidence?c. What is the standard time for changing tires if the allowance is 20 percent?
7. In the field of statistics, give an example of: a. A discrete variable. b. A continuous variable. c. A qualitative variable.
Which of the following can increase effect size? Select one: O a. increase the distance between means and increase the sample size O b. decrease the variability and increase the distance between means O c. decrease the variability and increase the sample size
Researchers have been studying acorns produced by trees in a certain region. The acorns are used as a food source by various animals. The researchers have recorded the mass of a random sample of acorns (displayed below). Acorn mass (grams): 4.1, 4.22, 3.9, 3.79, 4.09, 4.1, 4.03, 4.02, 3.78, 3.74, 3.72 Checksum: 43.49 Resample the sample (bootstrap) (link to program) with 1000 iterations to create a 90% confidence interval for the mean mass of all acorns: Result: The researchers can be 90% confident that the mean mass of all acorns in this region is between and grams.
3. Can SAT scores predict college performance? Let x be a variable that represents SAT score of a computer science major, and let y be a variable that represents a student’s GPA upon graduation. A random sample of n =15 computer science majors provided their SAT scores and GPAs: x 1232 1070 1086 1287 1130 1048 1121 1095 1135 1208 1333 1160 1186 1243 1261 y 3.52 2.91 2.4 3.47 3.47 2.37 2.4 2.24 3.02 3.32 3.59 2.54 3.19 3.71 3.58 The scatter diagram for the SAT score and GPA is given below: (a) Find the sample correlation coefficient r. Truncate to two decimal places. What does the value tell you about the data? (b) Find the equation of the least squares line . Truncate to four decimal places. What does the slope mean? (c) Find the value of the coefficient of determination . Truncate to two decimal places. What does this number mean? (d) What is the predicted GPA if a computer science major got a…
The age of first marriage for women who responded to a survey by the CDC between 2006 and 2010 is used here. The women who first married in their twenties were randomly divided into three groups: A, B, and C. The ANOVA output is supplied below: Count NAS (Missings) 3773 group Count A 1288 B 1246 C 1239 Frequency Source DF 2 group Residual 3770 28 26 24 Response Variable (age) Summary Mean 22 20 T 0 Group Variable Summary NAS Mean (Missings) 23.73787 A 0 23.76941 0 23.77929 0 23.66344 ANOVA Table: age-group Sum of Squares 10.283 26969 Mean Square Std. Dev. Std. Dev. 2.674442 B F Value Pr>F MSG 0.71875 0.48743 MSE Age of First Marriage in 20's 2.728097 2.664101 2.628699 C
c and d please
A governmental agency computed the proportion of violent crimes in the United States in a particular year falling into each of four categories. A simple random sample of 500 violent crimes committed in California during that year were categorized in the same way. The following table presents the results. Category U.S.Proportion CaliforniaFrequency Murder 0.018 4 Forcible Rape 0.07 35 Robbery 0.390 218 Aggravated Assault 0.522 243 Can you conclude that the proportions of crimes in the various categories in California differ from those in the United States as a whole? Use the 0.05 level of significance and the P-value method with the TI-84 Plus calculator. (b) Find the P-value. Round the answer to at least four decimal places.
A method or a set of procedures of using sample data to estimate a population parameter is called A. statistical inference B. statistical interference C. statistical appliance D. statistical description

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