A researcher wants to study the relationship between salary and gender. She randomly selects 218 individuals and determines their salary andgender. Can the researcher conclude that salary and gender are dependent?Male FemaleBelow $25,0001812$25,000-$50,0003523$50,000-$75,000 2660Above $75,000 2618105113IncomeTotalTotal30588644218Step 2 of 8: Find the expected value for the number of men with an income below $25,000. Round your answer to one decimal place.Copy Data

The row total of income below$25,000 is 30 and the column total of male is 105.

Answered: A researcher wants to study the…

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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How productive are U.S. workers? One way to answer this question is to study annual profits per employee. A random sample of companies in computers (I), aerospace (II), heavy equipment (III), and broadcasting (IV) gave the following data regarding annual profits per employee (units in thousands of dollars). I II III IV 27.9 13.5 22.2 17.9 23.2 9.6 20.5 16.4 14.7 11.1 7.7 14.5 8.3 8.9 12.7 15.9 11.8 6.5 7.7 10.6 19.1 9.5 What are the degrees of freedom? (numerator) (denominator)(c) Find the P-value of the sample test statistic. P-value > 0.100 0.050 < P-value < 0.100 0.025 < P-value < 0.050 0.010 < P-value < 0.025 0.001 < P-value < 0.010 P-value < 0.001 (d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Since the P-value is greater than the level of significance at α = 0.05, we do not reject H0. Since the P-value is less than or equal to the level of significance at α = 0.05, we…
Claim: Most adults would erase all of their personal information online if they could. A software firm survey of 475 randomly selected adults showed that 57% of them would erase all of their personal information online if they could. Find the value of the test statistic.
A statistics professor would like to build a model relating student scores on the first test to the scores on the second test. The test scores from a random sample of 2121 students who have previously taken the course are given in the table. Test Scores Student First Test Grade Second Test Grade 1 8989 7777 2 6060 7373 3 5252 6767 4 4444 6262 5 7474 7373 6 6969 7171 7 4343 6363 8 8080 7878 9 4747 6161 10 7676 7878 11 6565 7575 12 8989 7878 13 7878 7777 14 9696 8181 15 5252 6161 16 9393 8585 17 9090 8080 18 6767 6969 19 4343 6060 20 4848 6161 21 4646 6161 Copy Data Step 1 of 2: Using statistical software, estimate the parameters of the model Second Test Grade=β0+β1(First Test Grade)+εiSecond Test Grade=β0+β1(First Test Grade)+εi. Enter a negative estimate as a negative number in the regression model. Round your answers to 4 decimal places, if necessary.
Forbes magazine published data on the best small firms in 2012. These were firms that had been publicly traded for at least a year, have a stock price of at least $5 per share, and have reported annual revenue between $5 million and $1 billion. The table below shows the ages of the corporate CEOS for a random sample of these firms. 48 58 51 61 56 59 74 63 53 50 59 60 60 57 46 63 57 55 47 55 57 43 61 62 49 67 55 67 55 49 Use this sample data to construct a 90% confidence interval for the mean age of CEO's for these top small firms. Use the Student's t-distribution (a) what is the lower bound for 90% confidence interval for the mean age of CEO's? (Round to 3decimal places) UESTION 32 (b) What is the upper bound (Round to 3 decimla places)
A research group is conducting an experiment to study the relationship between fitness levels and the number of hours spent exercising each week. Subjects are randomly selected and, after several fitness tests, are assigned a fitness score. The number of hours spent exercising per week is also recorded. Data for 15 subjects are given below. Subject Hours of Exercise per Week Fitness Score 1 1 3 2 1.5 4.7 3 1.75 6 4 2 5 5 2 6.5 6 4.5 14.2 7 2.5 13.5 8 3.25 15 9 3 13.4 10 3.75 14 11 3.5 10 12 4 10 13 2.5 12 14 5.25 14.5 15 5 15 Create a bar graph in MicrosoftÂ® ExcelÂ® using the data. Label the graph and include the source of the data. Construct an equation in two variables that models this relationship. This equation may be linear, polynomial, rational, square root, or variation? Is the equation an exact model or an approximate model of the relationship between the variables? Explain your reasoning. Use the equation to make a prediction of the likely value of the…
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…
A firm wants to know if there is any difference in percentage of sport category watched based on age. The data for consumer preference can be found in the table below. What are the expected frequencies of each consumer entry? TV Viewers: % of Viewers, by Major Sport Category Item Ages 18-34 Ages 35+ eSports 50.6 86.3 Mixed Martial Arts 30 80.7 MLS 27.3 79.7 High School Football n/a 79.4 Minor League Hockey 24.6 78.8 Soccer (non-USA) 23.9 78.7 NBA 23.9 77.5 Running n/a 76.9 Minor League Baseball 21.7 76.7 NHL 20.1 73.9 NFL 20.1 70.5 NASCAR 19.3 n/a MLB 19.1 68.1 Tennis 18.7 68.5 College Basketball 18.2 n/a IndyCar 18 62.7 College Football 17.9 62.5 Golf 11.9 32
How do the average weekly incomes of electricians and carpenters compare? A random sample of 17 regions in the United States gave the following information about average weekly income (in dollars). (Reference: U.S. Department of Labor, Bureau of Labor Statistics.) Region 1 2 3 4 5 6 7 8 9 Electricians 464 715 597 464 736 694 744 571 806 Carpenters 542 813 513 476 688 503 789 653 474 Region 10 11 12 13 14 15 16 17 Electricians 592 594 702 579 868 598 597 654 Carpenters 489 647 676 384 817 605 556 505 Does this information indicate a difference (either way) in the average weekly incomes of electricians compared to those of carpenters? Use a 5% level of significance. (a) What is the level of significance? (b) Compute the sample test statistic. (c) Find the P-value of the sample test statistic.
Claim: Most adults would erase all of their personal information online if they could. A software firm survey of 455 randomly selected adults showed that 61% of them would erase all of their personal information online if they could. Find the value of the test statistic.
Claim: Most adults would erase all of their personal information online if they could. A software firm survey of 404 randomly selected adults showed that 65% of them would erase all of their personal information online if they could. Find the value of the test statistic.
A grocery store manager wants to estimate the mean purchase total for all customers that shop at her store. To do so, she selects a random sample of 30 receipts from the large list of all receipts that are stored in the computer. Here is a dotplot of the results. The mean purchase total is $93.80 and the median purchase total is $75.80. The store manager investigates and learns that the customer that made a $500 purchase had not purchased groceries, but rather a $500 gift card. Because this customer’s purchase was not typical, the manager decides to exclude this total from the data set. How will removing the $500 purchase from the data set affect the value of the mean and the median? (A) The mean will decrease more than the median. (B) The mean will decrease less than the median. (C) The mean will stay the same, but the median will decrease. (D) The mean will increase more than the median. (E) The mean will increase, but not as much as the median.

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