**Bivariate Analysis: Two-Way Table**In bivariate analysis, we examine the relationship between two variables. Here, we have collected data on two variables: salary and working hours from an underlying population.### Two-Way Table Example:We have data on salary, education, gender, and working hours from 10 employees of a tech company in Kabul.#### Employee Data:| Obs | Gender | Education | Salary | Working Hrs ||-----|--------|-----------|--------|-------------|| 1 | M | HS | 20 | 6 || 2 | M | HS | 30 | 7 || 3 | M | BA | 26 | 7 || 4 | F | MPH | 24 | 7 || 5 | F | PHD | 35 | 8 || 6 | M | MA | 36 | 7 || 7 | M | PHD | 30 | 8 || 8 | F | MA | 24 | 7 || 9 | F | HS | 30 | 6 || 10 | M | BA | 26 | 7 |### Two-Way Table: Working Hours and SalaryThis table displays the frequency distribution of employees based on their working hours and salary ranges.| | Sal<20 | [20-30) | Sal≥30 | Total ||---------------|--------|--------|-------|-------|| Whr<7 | 2 | 0 | 0 | 2 || [7,8) | 0 | 4 | 0 | 4 || Whr>8 | 0 | 0 | 4 | 4 || **Total** | **2** | **4** | **4** | **10**|### Multiple Choice Question:**Fr(Whr < 7, Sal ≥ 30) =**- [ ] 4- [ ] 0The frequency is 0, as there are no employees with working hours less than 7 and a salary of

Answered: To that end let X and Y to be two…

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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4.- For the following data set 10, 7, 6, k, 4, 7, 1, 10. Find the value of k so that (a) X = 6.25 (b) X = 7.5 Villalobos 2020 22 (c) M = 7 (d) MR = 10 CHAPTER 3. DATA DESCRIPTION
12. It can be small or large, as long as it includes all the data you are interested in.
26. Earlier in this chapter we described a study by Bartholow and Anderson (2002) examining how the experience of violence in video games influenced ag- gressive behavior for males and females. Their results suggest that increased violence increase aggressive behavior for males but has little or no effect for fe- males. The following data are measures of aggressive behavior similar to the results obtained in the study. Nonviolent Game Violent Game Female Male 3 6 2 2 4 7 9 9 4 8 10 8 9 4 5 8 4 6 12 16 13 17 13 13 a. Use an ANOVA with a = .05 to evaluate the data. Describe the effect of the violent game compared with a nonviolent game on the aggressive behavior for males and for females. b. Calculate the effect size (n²) for each main effect and for the interaction.
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47. The following table shows the scores on a clerical aptitude test and grades in a clerical skills course for 11 business administration students. Aptitude Test Score (x) 71 77 67 76 60 72 95 85 91 83 71 Skills Course Score (y) 73 85 74 82 70 83 92 85 97 89 79 a. Sketch the data using scatter diagram. b. Determine whether the data provide sufficient evidence to indicate that clerical aptitude test score and clerical skills course score are linearly related using 0.01 level of significance. C. Find the regression line. 48. The city engineer wants to establish the relationship between household size and monthly household water consumption. Given the data in the table, determine the following: Plot the data in a scatter plot and find the correlation r. Determine whether we can conclude from these data that the two variables are linearly related at 0.05 level of significance. Find the regression line. a. b. C. Household size (x) Gallons of Water Used (y) C. 3 3 4 8 7 655 700 500 800 600…
23 views A well-known multinational FMCG produces more than fifty products and sells them in the market. Out of fifty products one is mineral water for drinking purpose and supplies different size pack bottles in the market. Product manager observed that, during hot days the sale of water is more as compared to the normal days. He started the collection of data of weekly sale of water and the average weekly temperature. Product manager was interested in developing a relationship between sales and temperature; therefore, he discussed and shared the following data with you. sales 75 77 69 63 79 80 77 70 73 87 72 73 80 80 69 84 77 72 74 81 temperature 32 36 31 31 34 29 32 35 28 31 30 31 29 35 36 28 32 33 32 33 Sale is in thousand liters and temperature is in degree Celsius. Data is Normally distributed You are required to determine the following information for some concrete decision:…
Insurance (Life Expectancy). Insurance companies base their premiums on many factors, but basically all the factors are variables that predict life expectancy. Life expectancy varies from place to place. The following variables are from a data set on various measures obtained from the 50 US states (around 2009) Murder: rate per 100,000 HS Graduation: recorded as a percentage Income: per capita income in dollars Illiteracy: rate per 1,000 Life Expectancy: recorded in years 2008 Electoral vote state color: red / blue State electoral vote color coded: red = 1 / blue = 0 Multiple linear regression results: See Attachments please Write the multiple linear regression equation, use this equation to predict the Life expectancy for Pennsylvania and calculate the residual. Data: State Name Life Expectancy Murder HS Grad Income Illiteracy ColorCode Color Alabama 69.05 15.1 41.3 3624 2.1 1 red Alaska 69.31 11.3 66.7 6315 1.5 1 red Arizona 70.55 7.8 58.1 4530 1.8 1 red Arkansas…
Kindly answer question d) , e) and f)
1. A dietetics student wanted to look at the relationship between calcium intake and knowledge about calcium in sports science students. Table 1 shows the data she collected. Knowledge Respond ent Calcium intake Respond ent Knowledge Calcium intake score score (Out of 50) number (mg/day) number (Out of 50) (mg/day) 1 10 450 11 38 940 2 42 1050 12 25 733 3 38 900 13 48 985 4 15 525 14 28 763 5 22 710 15 22 583 6 32 854 16 45 850 7 40 800 17 18 798 8 14 493 18 24 754 9 26 730 19 30 805 10 32 894 20 43 1085 Is there a relationship between calcium intake and knowledge about calcium in sports science students?
Question 4Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of thecompany wants to know how different variables affect the sales of his vehicles. A random sample ofyearly data was taken with the view to testing the model:SALES=?+?AGE+?MIL+?ENGWhere SALES= amount that a vehicle is sold for($000’s), AGE = age of the vehicle, MIL= the totalmileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data wasprocessed using MINITAB and the following is an extract of the output obtained: d) Hence test whether ? is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term “R-sq” and comment on its value.
The authors of a paper compared two different methods for measuring body fat percentage. One method uses ultrasound, and the other method uses X-ray technology. Body fat percentages using each of these methods for 16 athletes (a subset of the data given in a graph that appeared in the paper) are given in the accompanying table. You can assume that the 16 athletes who participated in this study are representative of the population of athletes. Athlete X-ray Ultrasound 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 5.00 8.00 9.25 12.00 17.25 29.50 5.50 6.00 8.00 13.50 9.25 11.00 12.00 14.00 17.00 18.00 4.25 4.75 9.00 11.75 17.00 27.50 6.50 6.75 8.75 14.50 9.50 12.00 12.25 15.50 18.00 18.25 Use these data to estimate the difference in mean body fat percentage measurement for the two methods. Use a confidence level of 95%. (Use μ = MX-ray-Multrasound. Round your answers to three decimal places.) × % Interpret the interval in context. O There is a 95% chance that the true mean body fat percentage…

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