Looking at the tables for crosstabulation for Respondents Race, Highest Degree, and Respondents sex. How do we find out which one of these is the independent, dependent and or dummy variable? Also, how would you come up with an example for a Hypothesis for this? This is all one doccument. Table was too large. The first image is the top of the crosstab. **Respondents' Sex by Highest Degree and Race Crosstabulation**This table represents the distribution of respondents' highest educational degrees segmented by race and sex. The data is organized into several columns and rows, showing counts and percentages.### Key Sections#### Categories and Columns:1. **Race of Respondent**: - White - Black2. **Respondents’ Sex**: - Male - Female3. **RS Highest Degree**: - LT High School - High School - Junior College - Bachelor - Graduate#### Data Breakdown:**White Respondents:**- *Males*: - LT High School: 92 (13.4%) - High School: 327 (47.5%) - Junior College: 43 (6.2%) - Bachelor: 146 (21.2%) - Graduate: 81 (11.8%) - **Total**: 689 (100.0%)- *Females*: - LT High School: 103 (12.0%) - High School: 431 (50.1%) - Junior College: 59 (6.9%) - Bachelor: 173 (20.1%) - Graduate: 95 (11.0%) - **Total**: 861 (100.0%)- **Overall Total** (White): - Total Count: 1550 - Total Percentage: 100.0%**Black Respondents:**- *Males*: - LT High School: 8 (27.1%) - High School: 15 (50.8%) - Junior College: 2 (4.2%) - Bachelor: 13 (11.0%) - Graduate: 1 (6.8%) - **Total**: 39 (100.0%)- *Females*: - LT High School: 31 - High School: 102 - Junior College: 28 - Bachelor: 20 - Graduate: 12 - **Total**: 193 ### Notes:- Percentages are calculated within respondents' sex for each race category.- This data provides insights into educational attainment across different demographics. ### Image Transcription for Educational Use#### Table The table is segmented into different sections based on various racial categories, showing data on respondents' gender (Male, Female) and their distribution percentage, as well as the count within these categories.Each section includes:- **RACE OF RESPONDENT:** Divided into WHITE, BLACK, and OTHER.- **Respondents' Gender:** Data separated into Male and Female with percentage distributions within each gender across different categories.For example:- **WHITE Males:** - % within RESPONDENTS SEX: 16.1%, 52.8%, 14.5%, 10.4%, 6.2%, 100.0%- **WHITE Females:** - % within RESPONDENTS SEX: 20.3%, 52.1%, 10.6%, 10.6%, 6.4%, 100.0%Similar data structures are presented for Black and Other racial categories.#### Chi-Square TestsThis section contains statistical test results:- **Chi-Square Values:** Specific Chi-Square statistics for each RACE OF RESPONDENT, associated df (degrees of freedom), and Asymptotic Significance values. - Example: For WHITE respondents, Pearson Chi-Square value is 1.732 with an Asymptotic Significance of 0.785.- **Likelihood Ratios and Linear-by-Linear Association values** are also presented for each category.- **Remarks on Expected Count:** Notes indicating cells with expected counts less than 5 and the minimum expected counts for reference.#### Symmetric MeasuresThis section lists symmetric measure statistics for each racial category:- **Nominal by Nominal Measures:** Phi and Contingency Coefficient values with Asymptotic Significance values. - Example: For WHITE, Nominal by Nominal Phi value is 0.033.- **Ordinal by Ordinal Measures:** Gamma values with Zero-Order and associated significance and error values. - Includes Approximate t values for each measure, clarifying the statistical precision.- **Total Counts and Cases:** The data mentions the total number of valid cases applicable to each measure.#### Graphs or DiagramsThere are no graphs or diagrams in the image. The visual elements are entirely tabular data, focusing on statistical results and measures associated with respondents' race and gender.### Educational PerspectiveThis data is useful in understanding

Looking at the tables for crosstabulation for Respondents Race, Highest Degree, and Respondents sex. How do we find out which one of these is the independent, dependent and or dummy variable? Also, how would you come up with an example for

Looking at the tables for crosstabulation for Respondents Race, Highest Degree, and Respondents sex. How do we find out which one of these is the independent, dependent and or dummy variable? Also, how would you come up with an example for

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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