23SUDE 2 OF 3OatTo that end let X and Y to be two variables andsuppose we have collected data on both of themfrom an underlying population:X1.X2......XnV₁, V2, ..... YnTwo-way table can be constructed in threedifferent cases.678EX: We have collected data on Salary, Education,Gender, and Working Hours from all 10 employeesof a Tech company in Kabul.ObsGender Education Salary11022033045910MMFFFMMMMMHSBAMAMAPHDMABABivariate Analysis: Two way TableTwo way Table:1: Gender and Education:HSBA044BAHSBAPowerPoint Slide Show - (BivarPart1.pptx)-PowerPoint3550382523152613Working Hrs68991098767ACFOM2DMA213PHD101ATotal3710OE O& VENG 12:18 PMFr(Gender=F, Education=PHD)=1MULTIPLE CHOICE QUESTION3RewatchSubmitActivate WindowsGo to Settings to activate Windows.

P O To that end let X and Y to be two variables and suppose we have collected data on both of them from an underlying population: 2 Two-way table can be constructed in three different cases. 3 4 EX: We have collected data on Salary, Education, Gender, and Working Hours from all 10 employees of a Tech company in Kabul. Obs Gender Education Salary 10 1 10 20 30 35 50 M 38 5 6 7 8 9 10 M M F F F M M M M X1, X2, X Y₁.Y2...... Y M HS BA Bivariate Analysis: Two way Table Two way Table: 1: Gender and Education: HS BA 0 4 4 MA MA PHD MA PowerPoint Slide Show-varapp-PowerPoint BA BA HS BA DE 25 23 15 26 Working Hrs 6 8 9 9 10 9 8 7 6 F0 M2 D | ΜΑ 2 1 3 PHD 1 0 1 Total 3 7 10 OVA. ENG 12:18 PM Fr(Gender-F, Education=PHD)= 1 MULTIPLE CHOICE QUESTION 3 Rewatch Submit

P O To that end let X and Y to be two variables and suppose we have collected data on both of them from an underlying population: 2 Two-way table can be constructed in three different cases. 3 4 EX: We have collected data on Salary, Education, Gender, and Working Hours from all 10 employees of a Tech company in Kabul. Obs Gender Education Salary 10 1 10 20 30 35 50 M 38 5 6 7 8 9 10 M M F F F M M M M X1, X2, X Y₁.Y2...... Y M HS BA Bivariate Analysis: Two way Table Two way Table: 1: Gender and Education: HS BA 0 4 4 MA MA PHD MA PowerPoint Slide Show-varapp-PowerPoint BA BA HS BA DE 25 23 15 26 Working Hrs 6 8 9 9 10 9 8 7 6 F0 M2 D | ΜΑ 2 1 3 PHD 1 0 1 Total 3 7 10 OVA. ENG 12:18 PM Fr(Gender-F, Education=PHD)= 1 MULTIPLE CHOICE QUESTION 3 Rewatch Submit

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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Suppose you have access to a database with the variables listed below. Choose two variables you are interested in exploring that may be related (a predictor and outcome). Which variable is your y (outcome) and which is your x (predictor)? *Hint: which one may predict the other? Example: hot weather may predict sunburns.
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.
Suppose researchers at an abdominal transplant clinic are concerned about the rate of graft loss due to diabetes status prior to receiving a donor kidney. Research has shown that gender discordance, or receiving a gender from a donor of an opposite gender may increase the risk of both exposure and outcome after transplant. Assume the following tables represent the stratified analysis of the potential confounding variable. (9 points) Gender Discordance Graft Failure No Graft Failure Total Diabetes II 23 10 33 No Diabetes II 4 44 48 Total 27 54 81 Gender Concordance Graft Failure No Graft Failure Total Diabetes II 9 34 43 No Diabetes II 12 87 99 Total 21 121 142 A) Calculate the stratum specific estimates for the odds ratios in each strata. B) Observe the difference in the odds ratios. Based on observation alone, what are we likely to conclude regarding the relationship between outcome and exposure…
3. A scatter plot diagram is a: O Graphical technique that allows us to determine the cause and effect relationship and the degree of relationship between two quantitative variables O Graphical technique that allows us to determine the association and the degree of relationship between two quantitative variables O Numerical technique that allows us to determine the relationship as well as the degree of relationship between two quantitative variables Numerical technique that allows us to determine the cause and effect relationship and the degree of relationship between two quantitative variables
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:…
Your state is going to vote on becoming a "right to work" state in the next, and you wonder if there is there a relationship between salary levels and unionization. You find data on salary from the U.S. Census, which is split into three groups: Low; Moderate/About Average, and; High. To see if salary, measured in this way, is associated with unionization you find a variable in the same dataset called "UNION", which has two categories: the respondent has a unionized job and the respondent does not have a unionized job. Because you want to know if you should favor or oppose becoming a "right to work" state, you test these two variables to see if there is an association between salary level and unionized labor. What type of hypothesis test is most appropriate?
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?
Do question iii and iv only.
. Present a description of your variables: Provide a codebook with the following four columns: (1) Variable name; (2) Variable label; (3) Value & Value label and Level of measurement (i.e., nominal, ordinal, interval, ratio). Please present this as a table. This should fit on one page.
This dataset of size n - 51 is for the 50 states and the District of Columbia in the United States. The variables are - year 2002 birth rate per 1000 females 15 to 17 years old and z- poverty rate (the percent of the state's population living in households with in- comes below the federally defined poverty level) i- 13.1 - 22.3 R- 51, Su - E(-2) - 914.7 S, - E( -2)( - 6) - 1, 256.2 Su - E(m - M) - 3, 249 SSE - E(w - - 1, 509.6 1. Find A. A and r. 2. Write the fitted linear regression model for ý, in terms of z, A, and A- For A and , use the values you obtained in problem 1. 3. Interpret the slope of the least squares line based on the context. 4. Find SST, SE and SSR. 5. Find R* and . 6. Complete a chart for ANOVA df MS pvalue Source Regression Error Total 7. Complete a chart for Parameter Estimates. t-value pvalue Parameter Intercept Slope Estimate S.e. 8. What is the residual e, for the observation (.) - (20.1,31.5)? 9. What is the conclusion for the test Ha : -0 vs Ho : +0 with a -…
Do question i and ii only.