Format Column Variable Name Label Codes Subject's Identification ABCD ID Sex Number N/A X Subject Sex Identified at Birth M= Male; F=Female X Age Age at time of Visit Range 0-100 X BMI Body Mass Index at Visit 0-70 X E Income Annual Income Range 0-10,000; >10,000-30,000; >30,000-50,000; >50,000- 100,00; >100,000 >HS; HS or equivalent; Some College; College or Graduate School F Education Level of Education G Systolic Blood Pressure SBP reading at Visit 0-200 H Employment Diabetes J TV K Physical M Housing N Zipcode Subject Employment Status Self-Reported Diabetes Status Time Spent watching TV per day in hours Time Spent working out per week in hours Housing Status Zip code of Current or Last Residence Unemployed; Employed X X X part-time; full-time employment X Y=Yes; N=No X 0-24 0-168 0=rent; 1=Own; 2-Unhoused; 3=Living with Friends or Family N/A X X X X

Format Column Variable Name Label Codes Subject's Identification ABCD ID Sex Number N/A X Subject Sex Identified at Birth M= Male; F=Female X Age Age at time of Visit Range 0-100 X BMI Body Mass Index at Visit 0-70 X E Income Annual Income Range 0-10,000; >10,000-30,000; >30,000-50,000; >50,000- 100,00; >100,000 >HS; HS or equivalent; Some College; College or Graduate School F Education Level of Education G Systolic Blood Pressure SBP reading at Visit 0-200 H Employment Diabetes J TV K Physical M Housing N Zipcode Subject Employment Status Self-Reported Diabetes Status Time Spent watching TV per day in hours Time Spent working out per week in hours Housing Status Zip code of Current or Last Residence Unemployed; Employed X X X part-time; full-time employment X Y=Yes; N=No X 0-24 0-168 0=rent; 1=Own; 2-Unhoused; 3=Living with Friends or Family N/A X X X X

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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The following table was generated from the sample data of 1010 junior high students regarding the average number of hours they are unsupervised per night, the average number of hours they play video games per night, and their final grades in their math class. The dependent variable is the final grade, the first independent variable (x1x1) is the number of hours unsupervised each night, and the second independent variable (x2x2) is the number of hours of video games each night. Coefficients Standard Error t-Stat p-value Intercept 57.968435 7.227955 8.020032 0.000201 Hours Unsupervised 5.131630 1.314283 3.904510 0.007943 Hours Playing Video Games 1.067855 1.615039 0.661194 0.533040 Write the multiple regression equation for the computer output given. Round your answers to three decimal places.
The following table was generated from the sample data of 10 junior high students regarding the average number of hours they are unsupervised per night, the average number of hours they play video games per night, and their final grades in their math class. The dependent variable is the final grade, the first independent variable (x1) is the number of hours unsupervised each night, and the second independent variable (x2) is the number of hours of video games each night. Coefficients Standard Error t-Stat p-value Intercept 62.711817 4.607133 13.611896 0.000010 Hours Unsupervised 0.635048 0.915495 0.693666 0.513836 Hours Playing Video Games 7.528738 1.296727 5.805955 0.001145 Copy Data Step 1 of 2: Write the multiple regression equation for the computer output given. Round your answers to three decimal places. Answer 田 Tables 国 Keypad How to enter your answer (opens in new window) Keyboard Shortcuts X +
Twelve husbands were asked how much housework they completed last week and how many children were in the home. Use the following data to complete the questions in this section. Write out the linear model. Children Husband’s Housework Children Husband’s Housework 2 4 4 6 1 1 1 3 3 0 3 5 5 4 2 3 1 5 2 1 5 7 4 3
The relative effectiveness of two different sales techniques was tested on 12 volunteer housewives. Each housewife was exposed to each sales technique and asked to buy a certain product, the same product in all cases. At the end of each exposure, each housewife rated the technique with a 1 if she felt she would have agreed to buy the product and a 0 if she probably would not have bought the product. Tech 1 2 3 4 1 1 1 2 0 1 1 1 1 0 5 6 7 8 9 10 1 Housewife 0 0 0 0 0 Test Ho: P₁=p₂ versus H₂: P₁ P₂ Use large sample approximations and compare results. 0 0 1 1 1 0 11 12 01 0 1 a) Use Cochran's test b) Rearrange the data and use McNemar's test c) use Fischer exact test d)Ignore the blocking effect in this experiment and treat the data as if 24 difference housewives were used.
state the degrees of freedom if necessary
The following table was generated from the sample data of 1010 junior high students regarding the average number of hours they are unsupervised per night, the average number of hours they play video games per night, and their final grades in their math class. The dependent variable is the final grade, the first independent variable (x1x1) is the number of hours unsupervised each night, and the second independent variable (x2x2) is the number of hours of video games each night. Coefficients Standard Error t-Stat p-value Intercept 57.968435 7.227955 8.020032 0.000201 Hours Unsupervised 5.131630 1.314283 3.904510 0.007943 Hours Playing Video Games 1.067855 1.615039 0.661194 0.533040 Indicate if any of the independent variables could be eliminated at the
You have the following data: Student A took 2 courses in the Fall semester. His previous CGPA was 3.2. He received GPA 3.5 in the Fall semester. Student B took 5 courses in the Fall semester. Her previous CGPA was 3.9. She received GPA 3.6 in the Fall semester. Student C took 4 courses in the Fall semester. His previous CGPA was 3.6. He received GPA 3.4 in the Fall semester. Using this data, we'll try to build a model using Least Square approximation, that can predict the CGPA of a student in the Fall semester given the number of courses s/he took in Fall, and his/her previous CGPA. (In real life, we'd use many more parameters, but for the sake of the quiz, we are keeping things simple.) The model is as follows - wi x (number of courses) + wz x (previouos CGPA) = GPA in Fall Find the values of wi, and wz using Least Square approximation. (Round off up to 3 decimal points) w, is equal to - wz is equal to - If a student took 4 courses in Fall, and his previous CGPA was 3.7, what would be…
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