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NU Statistical Analysis Discussion
Overview and RationaleIn this project, you will design a prescriptive model for an inventory problem. Furthermore, you wil ...
NU Statistical Analysis Discussion
Overview and RationaleIn this project, you will design a prescriptive model for an inventory problem. Furthermore, you will obtain “optimal” solution(s) of your model both in the absence and the presence of uncertainty.Problem:Inventories represent a considerable investment for every organization; thus, it is important that they be managed well. Excess inventories can indicate poor financial and operational management. On the other hand, not having inventory when it is needed can also result in business failure. The two basic inventory decisions that managers face are how much to order or produce for additional inventory, and when to order or produce it to minimize total inventory cost, which consists of the cost of holding inventory and the cost of ordering it from the supplier.
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.
Walden University SAS Studio Task
Overview
Blood pressure is the force of blood pushing against the walls of the arteries that carry blood from your heart t ...
Walden University SAS Studio Task
Overview
Blood pressure is the force of blood pushing against the walls of the arteries that carry blood from your heart to other parts of your body. Blood pressure normally rises and falls throughout the day, but it can damage your heart and cause health problems if it stays high for a long time. Keeping your blood pressure levels in a healthy range usually involves taking medications among other things.
In this part, you will work with a set of data that is obtained by testing a new drug for blood pressure. The data consists of information collected on 50 patients on the following variables:
Subject: Patient
Treatment: Two levels. 0 for Placebo and 1 for treatment group
Gender: Male or Female
Fam-Hist-BP: Paternal Side - PS, Maternal Side - MS,
Both Sides – BS, None on both sides (or not known) – N
Age: Age of patient
BP-Before-Exp: Blood Pressure before experiment
BP-After- Exp: Blood Pressure after experiment
Do the following
Data: Download the NEW DRUG DATA (see attachment) and study the data.
Review Using the Import Data Utility in SAS Studio (Links to an external site.)to learn how to import Excel data files into SAS Studio.
Required Action: Based on the data set provided, produce the following output with SAS (or SPSS):
Generate frequency tables for three categorical variables.
Generate at least two different cross-tabulations.
Generate a pareto chart for the categorical variable Fam-Hist-BP.
Find the five number summary, mean, and standard deviation for three quantitative variables.
Generate a side by side boxplot to compare the variables BP-Before-Exp and BP-After-Exp.
Generate a histogram for each of the quantitative variables.
Generate a scatterplot to display the relationship and find the correlation between Age and BP-Before-Exp.
Generate a scatterplot to display the relationship and find the correlation between BP-Before-Exp and BP-After-Exp.
MAT 243 SNHU Python Script Output Discussion
Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one o ...
MAT 243 SNHU Python Script Output Discussion
Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one of the industry-specific ETFs is significantly different. Use a 5% level of significance.In your initial post, address the following items:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 2 in the Python script.Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script.Attached is the data needed to answer the questions.
QNT561 University of Phoenix Week 5 SpeedX Payment Times Case Study
Create a Minimum 750 word statistical analysis based on BOTH the Case Study Scenarios and SpeedX Payment Times. Address th ...
QNT561 University of Phoenix Week 5 SpeedX Payment Times Case Study
Create a Minimum 750 word statistical analysis based on BOTH the Case Study Scenarios and SpeedX Payment Times. Address the followingCase 1: Election Results Use 0.10 as the significance level (α).Conduct a one-sample hypothesis test to determine if the networks should announce at 8:01 P.M. the Republican candidate George W. Bush will win the state. Case 2: SpeedXUse 0.10 and the significance level (α).Conduct a one-sample hypothesis test and determine if you can convince the CFO to conclude the plan will be profitable.
Create a Tableau File
Please follow the instructions attached below to create the files required. Please message me if you have any questions. S ...
Create a Tableau File
Please follow the instructions attached below to create the files required. Please message me if you have any questions. Since I'm going to do a video explaining the project. I attached a sample of a video that someone is explaining it. So I need the same explanation of how you did it in a word so I could explain it in the video step by step please. Also keep the video as an example of the project. https://www.youtube.com/watch?v=UQp6Cq4S4CU&feature=youtu.be
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NU Statistical Analysis Discussion
Overview and RationaleIn this project, you will design a prescriptive model for an inventory problem. Furthermore, you wil ...
NU Statistical Analysis Discussion
Overview and RationaleIn this project, you will design a prescriptive model for an inventory problem. Furthermore, you will obtain “optimal” solution(s) of your model both in the absence and the presence of uncertainty.Problem:Inventories represent a considerable investment for every organization; thus, it is important that they be managed well. Excess inventories can indicate poor financial and operational management. On the other hand, not having inventory when it is needed can also result in business failure. The two basic inventory decisions that managers face are how much to order or produce for additional inventory, and when to order or produce it to minimize total inventory cost, which consists of the cost of holding inventory and the cost of ordering it from the supplier.
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.
Walden University SAS Studio Task
Overview
Blood pressure is the force of blood pushing against the walls of the arteries that carry blood from your heart t ...
Walden University SAS Studio Task
Overview
Blood pressure is the force of blood pushing against the walls of the arteries that carry blood from your heart to other parts of your body. Blood pressure normally rises and falls throughout the day, but it can damage your heart and cause health problems if it stays high for a long time. Keeping your blood pressure levels in a healthy range usually involves taking medications among other things.
In this part, you will work with a set of data that is obtained by testing a new drug for blood pressure. The data consists of information collected on 50 patients on the following variables:
Subject: Patient
Treatment: Two levels. 0 for Placebo and 1 for treatment group
Gender: Male or Female
Fam-Hist-BP: Paternal Side - PS, Maternal Side - MS,
Both Sides – BS, None on both sides (or not known) – N
Age: Age of patient
BP-Before-Exp: Blood Pressure before experiment
BP-After- Exp: Blood Pressure after experiment
Do the following
Data: Download the NEW DRUG DATA (see attachment) and study the data.
Review Using the Import Data Utility in SAS Studio (Links to an external site.)to learn how to import Excel data files into SAS Studio.
Required Action: Based on the data set provided, produce the following output with SAS (or SPSS):
Generate frequency tables for three categorical variables.
Generate at least two different cross-tabulations.
Generate a pareto chart for the categorical variable Fam-Hist-BP.
Find the five number summary, mean, and standard deviation for three quantitative variables.
Generate a side by side boxplot to compare the variables BP-Before-Exp and BP-After-Exp.
Generate a histogram for each of the quantitative variables.
Generate a scatterplot to display the relationship and find the correlation between Age and BP-Before-Exp.
Generate a scatterplot to display the relationship and find the correlation between BP-Before-Exp and BP-After-Exp.
MAT 243 SNHU Python Script Output Discussion
Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one o ...
MAT 243 SNHU Python Script Output Discussion
Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one of the industry-specific ETFs is significantly different. Use a 5% level of significance.In your initial post, address the following items:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 2 in the Python script.Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script.Attached is the data needed to answer the questions.
QNT561 University of Phoenix Week 5 SpeedX Payment Times Case Study
Create a Minimum 750 word statistical analysis based on BOTH the Case Study Scenarios and SpeedX Payment Times. Address th ...
QNT561 University of Phoenix Week 5 SpeedX Payment Times Case Study
Create a Minimum 750 word statistical analysis based on BOTH the Case Study Scenarios and SpeedX Payment Times. Address the followingCase 1: Election Results Use 0.10 as the significance level (α).Conduct a one-sample hypothesis test to determine if the networks should announce at 8:01 P.M. the Republican candidate George W. Bush will win the state. Case 2: SpeedXUse 0.10 and the significance level (α).Conduct a one-sample hypothesis test and determine if you can convince the CFO to conclude the plan will be profitable.
Create a Tableau File
Please follow the instructions attached below to create the files required. Please message me if you have any questions. S ...
Create a Tableau File
Please follow the instructions attached below to create the files required. Please message me if you have any questions. Since I'm going to do a video explaining the project. I attached a sample of a video that someone is explaining it. So I need the same explanation of how you did it in a word so I could explain it in the video step by step please. Also keep the video as an example of the project. https://www.youtube.com/watch?v=UQp6Cq4S4CU&feature=youtu.be
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