Description
{2p^4y^4 / s^4}^4
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
Explanation & Answer
2^4 p^16 y^16 /s^16= 16 (py/s)^16
Completion Status:
100%
Review
Review
Anonymous
I use Studypool every time I need help studying, and it never disappoints.
Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4
24/7 Homework Help
Stuck on a homework question? Our verified tutors can answer all questions, from basic math to advanced rocket science!
Most Popular Content
Statistics Question
InstructionsPart 1: Using the Gun Control dataset complete the following tasks:Run a t-test on the variables: OwnGun, Amer ...
Statistics Question
InstructionsPart 1: Using the Gun Control dataset complete the following tasks:Run a t-test on the variables: OwnGun, AmericanOwn.Identify the:null hypothesis.research hypothesis.t-statistic.degrees of freedom.p-value.Summarize your findings.Part 2: Using the Gun Control dataset complete the following tasks:Run an ANOVA on the variables: Religion, AmericanOwn.Identify the:null hypothesis.research hypothesis.F-statistic.degrees of freedom.p-value.Summarize your findings.
MATH125 AIU Counting Techniques and Probability Paper
All questions have to be answered and show all step by step calculations. Text book used is General College Math by editor ...
MATH125 AIU Counting Techniques and Probability Paper
All questions have to be answered and show all step by step calculations. Text book used is General College Math by editorial board, Words of Wisdom.
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is wo ...
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is worth examining further. During Week 5, we studied tests of significance. In this week's discussion, we will apply these tests of significance to our project variables. We will also run measures of association to determine the strength and direction of the relationship between our variables. As we discussed previously, the levels of measurement of our variables determine which test of significance works for the research project. Here is the guideline: 1. Before-and-after design and the DV is at I/R level: Dependent Sample T-test2. DV and IV are BOTH categorical variables (nominal/ordinal): Chi-square*Special note for Chi-square: you should have less than 20% of the cells with an expected count of 5 or less. This information is reported automatically, right below the chi-square output table. If your chi-square test fails to meet this requirement, it is necessary to use "recoding" to combining certain answer categories together so the expected counts would increase. 3. DV and IV are both continuous (interval/ratio) variables: regression4. Comparison of groups (when IV is categorical - nominal/ordinal and DV is continuous - interval/ratio): a. Between 2 groups: Independent Sample T-test b. Among 3 or more groups: ANOVAWhy do we need to run tests of significance?They allow us to see if our relationship is "statistically significant." To be more specific, these tests tell us if a relationship observed in a sample, like your research project based on GSS 2016 data set, is generalizable to the population from which this sample was drawn (US adults).Test results reported under "p" in the SPSS output tells us the chances that a relationship observed in the sample is not real, but rather due to factors like a sampling error. We compare this "chance" with level of significance, commonly set as .05 or .01. If this chance is smaller than level of significance, we can reject the null hypothesis, and keep the research hypothesis.Next, we'll use tests of "measures of association" to figure out the exact strength of a relationship between two variables. In addition, we'll learn how to interpret SPSS outputs for measures of association tests such as lambda, gamma, and Pearson's r, along with other possible tests. These tests are also specific to the level of measurement of your variables. Here are the guidelines:Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)If it is a 2X2 table: PhiBoth DV and IV are ordinal variables: GammaOne variable ordinal AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): GammaOne variable ordinal AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer's V.Both DV and IV are I/R variables: Pearson's rTo interpret the output, see attached handout. Keep in mind measures of association is a statistical procedure based on Proportional Reduction of Error (PRE). Thus the format of interpretation will be: Knowing the IV will reduce error in predicting the DV by *%. Please note: Don't just say "IV" and "DV" in your explanation. You need to enter your variables names for IV and DV, and replace * for the exact test value from the output. If the value of Lambda is .34, then it will be interpreted as 34%.****Ok, now it is time for you to try! For this week's discussion, be sure to perform the correct test of significance (choose one) and measure of association (choose one) on your variables for the final project. You can download the class handout attached at the bottom of the page.This week in the discussion:I. You will decide which test of significance you will use for your project. Use the guideline above to make your choice.II. You will use the process for hypothesis testing which outlines five steps:Write your research hypothesis (H1) and your null hypothesis (H0).Identify and record your level of significance (alpha): either .05 or .01.Complete the significance test using SPSS. (Include the output of the analysis (table) in your post.)Identify the number under Sig. (2-tail). This will be represented by "p." Compare the numbers in steps 2 (alpha) and 4 (p) and apply the following rule:If p < or = alpha, than you reject the null hypothesisDetermine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain what that means to your research.III. You will decide which measure of association you will use for your project. Use the guideline above to make your choice. Include the output (table) in your post. Based on the output, describe the strength and direction of the relationship between the variables. Also explain the PRE.**** I have attached information about my variables "satjob1 and happy". the gss 2018 spreadsheet that contains both my variables and a helpful handout from class.
PUBH 8500 WU WK 10 Numeric Descriptive Statistics Census Region Analysis
Assignment: The Effect of Weights
“The use of sampling weights and sample design variables is recommended for all analys ...
PUBH 8500 WU WK 10 Numeric Descriptive Statistics Census Region Analysis
Assignment: The Effect of Weights
“The use of sampling weights and sample design variables is recommended for all analyses because the sample design is a clustered design and incorporates differential probabilities of selection. If you fail to account for the sampling parameters, you may obtain biased estimates and overstate significance levels.”
In other words, samples selected for surveys may have imperfections in their representation of the reference population. Imperfections include the selection of sampling unit with unequal probability, non-coverage of the population, and non-responses to survey questions. Sampling weights would be used to compensate for these imperfections and produce valid and reliable results.
For this Assignment, you analyze the relationship of two variables with logistic regression, using both weighted and unweighted data. You then compare the results to identify the effect of weighting on the interpretation of the relationship.
The Assignment
Examine the Data (30 Points)
Open the Week 10 Dataset (SPSS document) located in the Learning Resources area.
Produce numeric descriptive statistics for the following variables:
Cregion
USR
Sex
Q1
Q6a
Q16
Q22a
Receduc
Race/Ethnicity
Logistic Regression
Use SPSS to run a logistic regression model with Q22a. “Have you ever looked online for -- Information about a specific disease or medical problem?” as your dependent variable (Note that there are 4 levels of responses possible, but only 2 are actually used in the responses so you can state the dependent variable is a binomial and use binary logistic regression) and Sex as the independent variable.
Use backwards stepwise regression to add Receduc to the model as a potential confounder.
How does the relationship between Q22a and Sex change with the addition of Receduc? Include a discussion of Odds Ratios and the Model Summary in your answer. Would you consider Receduc a confounder? Is it worth keeping it in the model even if it does not coufound the relationship between Q22a and Sex in this sample?
Logistic Regression with weights
Weight cases using the variable standwt (Standardized weight)
Use SPSS to rerun a logistic regression model with Q22a. “Have you ever looked online for -- Information about a specific disease or medical problem?” as your dependent variable, Sex as the independent variable, and Receduc as a covariate.
How does weighting the cases change the outcome of the logistic regression?
Discuss why it is important to weight cases from surveys with complex sampling schemes using the differing outcomes you have from parts 2 and 3 of this assignment.
Similar Content
I need help with a math question
I need help with a math question...
San Jose State University Find the Trigonometric Values Mathematical Questions
Hello!
Can you please prove the following
Thx in advance...
Simple Regression in R Programming Language Coding Task
Hi,This assignment is a simple regression and will be focusing only on testing hypotheses using a single independent varia...
Hyperbolic Trig Functions and L’hopital Rule Worksheet
please answer these 4 questions. i already know the answers but i need work shown and explaination for each please!!! you ...
Help with Aleks Statistics Pie
Hello I need assistance completing my Statistics Pie. The class is Statistics 300 and must be completed through the online...
Find the slopes of the lines that are parallel and pereindicular to the line through the pair of poi
Find the slopes of the lines that are parallel and pereindicular to the line through the pair of points (-3,-3) and (-5,-5...
Dot Lanes To Build Ppg1987
Payoff Table (Cost of Each Outcome in MM of 2014 Dollars) b) As shown in the table below, the decision which would result...
34 Trigonometry
...
Statistics
source product inquieries from the internet had been decreased from 15% to 10% Hooper receive 192.25/525=0.366 wich means ...
Related Tags
Book Guides
Get 24/7
Homework help
Our tutors provide high quality explanations & answers.
Post question
Most Popular Content
Statistics Question
InstructionsPart 1: Using the Gun Control dataset complete the following tasks:Run a t-test on the variables: OwnGun, Amer ...
Statistics Question
InstructionsPart 1: Using the Gun Control dataset complete the following tasks:Run a t-test on the variables: OwnGun, AmericanOwn.Identify the:null hypothesis.research hypothesis.t-statistic.degrees of freedom.p-value.Summarize your findings.Part 2: Using the Gun Control dataset complete the following tasks:Run an ANOVA on the variables: Religion, AmericanOwn.Identify the:null hypothesis.research hypothesis.F-statistic.degrees of freedom.p-value.Summarize your findings.
MATH125 AIU Counting Techniques and Probability Paper
All questions have to be answered and show all step by step calculations. Text book used is General College Math by editor ...
MATH125 AIU Counting Techniques and Probability Paper
All questions have to be answered and show all step by step calculations. Text book used is General College Math by editorial board, Words of Wisdom.
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is wo ...
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is worth examining further. During Week 5, we studied tests of significance. In this week's discussion, we will apply these tests of significance to our project variables. We will also run measures of association to determine the strength and direction of the relationship between our variables. As we discussed previously, the levels of measurement of our variables determine which test of significance works for the research project. Here is the guideline: 1. Before-and-after design and the DV is at I/R level: Dependent Sample T-test2. DV and IV are BOTH categorical variables (nominal/ordinal): Chi-square*Special note for Chi-square: you should have less than 20% of the cells with an expected count of 5 or less. This information is reported automatically, right below the chi-square output table. If your chi-square test fails to meet this requirement, it is necessary to use "recoding" to combining certain answer categories together so the expected counts would increase. 3. DV and IV are both continuous (interval/ratio) variables: regression4. Comparison of groups (when IV is categorical - nominal/ordinal and DV is continuous - interval/ratio): a. Between 2 groups: Independent Sample T-test b. Among 3 or more groups: ANOVAWhy do we need to run tests of significance?They allow us to see if our relationship is "statistically significant." To be more specific, these tests tell us if a relationship observed in a sample, like your research project based on GSS 2016 data set, is generalizable to the population from which this sample was drawn (US adults).Test results reported under "p" in the SPSS output tells us the chances that a relationship observed in the sample is not real, but rather due to factors like a sampling error. We compare this "chance" with level of significance, commonly set as .05 or .01. If this chance is smaller than level of significance, we can reject the null hypothesis, and keep the research hypothesis.Next, we'll use tests of "measures of association" to figure out the exact strength of a relationship between two variables. In addition, we'll learn how to interpret SPSS outputs for measures of association tests such as lambda, gamma, and Pearson's r, along with other possible tests. These tests are also specific to the level of measurement of your variables. Here are the guidelines:Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)If it is a 2X2 table: PhiBoth DV and IV are ordinal variables: GammaOne variable ordinal AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): GammaOne variable ordinal AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer's V.Both DV and IV are I/R variables: Pearson's rTo interpret the output, see attached handout. Keep in mind measures of association is a statistical procedure based on Proportional Reduction of Error (PRE). Thus the format of interpretation will be: Knowing the IV will reduce error in predicting the DV by *%. Please note: Don't just say "IV" and "DV" in your explanation. You need to enter your variables names for IV and DV, and replace * for the exact test value from the output. If the value of Lambda is .34, then it will be interpreted as 34%.****Ok, now it is time for you to try! For this week's discussion, be sure to perform the correct test of significance (choose one) and measure of association (choose one) on your variables for the final project. You can download the class handout attached at the bottom of the page.This week in the discussion:I. You will decide which test of significance you will use for your project. Use the guideline above to make your choice.II. You will use the process for hypothesis testing which outlines five steps:Write your research hypothesis (H1) and your null hypothesis (H0).Identify and record your level of significance (alpha): either .05 or .01.Complete the significance test using SPSS. (Include the output of the analysis (table) in your post.)Identify the number under Sig. (2-tail). This will be represented by "p." Compare the numbers in steps 2 (alpha) and 4 (p) and apply the following rule:If p < or = alpha, than you reject the null hypothesisDetermine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain what that means to your research.III. You will decide which measure of association you will use for your project. Use the guideline above to make your choice. Include the output (table) in your post. Based on the output, describe the strength and direction of the relationship between the variables. Also explain the PRE.**** I have attached information about my variables "satjob1 and happy". the gss 2018 spreadsheet that contains both my variables and a helpful handout from class.
PUBH 8500 WU WK 10 Numeric Descriptive Statistics Census Region Analysis
Assignment: The Effect of Weights
“The use of sampling weights and sample design variables is recommended for all analys ...
PUBH 8500 WU WK 10 Numeric Descriptive Statistics Census Region Analysis
Assignment: The Effect of Weights
“The use of sampling weights and sample design variables is recommended for all analyses because the sample design is a clustered design and incorporates differential probabilities of selection. If you fail to account for the sampling parameters, you may obtain biased estimates and overstate significance levels.”
In other words, samples selected for surveys may have imperfections in their representation of the reference population. Imperfections include the selection of sampling unit with unequal probability, non-coverage of the population, and non-responses to survey questions. Sampling weights would be used to compensate for these imperfections and produce valid and reliable results.
For this Assignment, you analyze the relationship of two variables with logistic regression, using both weighted and unweighted data. You then compare the results to identify the effect of weighting on the interpretation of the relationship.
The Assignment
Examine the Data (30 Points)
Open the Week 10 Dataset (SPSS document) located in the Learning Resources area.
Produce numeric descriptive statistics for the following variables:
Cregion
USR
Sex
Q1
Q6a
Q16
Q22a
Receduc
Race/Ethnicity
Logistic Regression
Use SPSS to run a logistic regression model with Q22a. “Have you ever looked online for -- Information about a specific disease or medical problem?” as your dependent variable (Note that there are 4 levels of responses possible, but only 2 are actually used in the responses so you can state the dependent variable is a binomial and use binary logistic regression) and Sex as the independent variable.
Use backwards stepwise regression to add Receduc to the model as a potential confounder.
How does the relationship between Q22a and Sex change with the addition of Receduc? Include a discussion of Odds Ratios and the Model Summary in your answer. Would you consider Receduc a confounder? Is it worth keeping it in the model even if it does not coufound the relationship between Q22a and Sex in this sample?
Logistic Regression with weights
Weight cases using the variable standwt (Standardized weight)
Use SPSS to rerun a logistic regression model with Q22a. “Have you ever looked online for -- Information about a specific disease or medical problem?” as your dependent variable, Sex as the independent variable, and Receduc as a covariate.
How does weighting the cases change the outcome of the logistic regression?
Discuss why it is important to weight cases from surveys with complex sampling schemes using the differing outcomes you have from parts 2 and 3 of this assignment.
Earn money selling
your Study Documents