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need help with this problem please
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Factor out 4, 4(x^2-9x+20)
-5 and -4 add up to 9 so
If you factor the problem, you get 4 (x-4)(x-5)=0
Solutions are x-4=0, x-5=0
X=4,x=5
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ITEC 8437 WU Inferential Statistics One Sample T Test Male Professors Age Essay
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ITEC 8437 WU Inferential Statistics One Sample T Test Male Professors Age Essay
A t test examines if two means (averages) are reliably different from each other; that is, whether any significant differences exist between the means of samples from different populations. For example, to what extent is the output of a local office which applied an IT solution different than the output of other local offices which did not apply the IT solution? Also, if you wanted to test whether the average IQ score of a group of students differs from 100, you may use a t test. A t test does more than just compare means; as an inferential statistic, t tests allow researchers to make inferences about the populations beyond their sample data.For this Assignment, you will use the IT Security database and conduct two t tests: (a) one-sample t test and (b) paired-samples t test and prepare an APA results write-up for each test....thank you
UC San Diego Management 3: Quantitative Methods in Business
The questions are attched This is a simulation exercise in R. you’ll be creating simulated data in this exercise
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Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for ...
Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the housing prices based square footage. To complete this task, use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided.DirectionsUsing the Project One Template located in the What to Submit section, generate a report including your tables and graphs to determine if the square footage of a house is a good indicator for what the listing price should be. Reference the National Statistics and Graphs document for national comparisons and the Real Estate Data spreadsheet (both found in the Supporting Materials section) for your statistical analysis.Note: Present your data in a clearly labeled table and using clearly labeled graphs.Specifically, include the following in your report:IntroductionDescribe the report: Give a brief description of the purpose of your report.Define the question your report is trying to answer.Explain when using linear regression is most appropriate.When using linear regression, what would you expect the scatterplot to look like?Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.Data CollectionSampling the data: Select a random sample of 50 houses.Identify your response and predictor variables.Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model.Data AnalysisHistogram: For your two variables, create histograms.Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.Interpret the graphs and statistics:Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables.Compare and contrast the shape, center, spread, and any unusual characteristic for your sample of house sales with the national population. Is your sample representative of national housing market sales?Develop Your Regression ModelScatterplot: Provide a graph of the scatterplot of the data with a line of best fit.Explain if a regression model is appropriate to develop based on your scatterplot.Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.Identify any possible outliers or influential points and discuss their effect on the correlation.Discuss keeping or removing outlier data points and what impact your decision would have on your model.Find r: Find the correlation coefficient (r).Explain how the r value you calculated supports what you noticed in your scatterplot.Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables.Interpret regression equation: Interpret the slope and intercept in context.Strength of the equation: Provide and interpret R-squared.Determine the strength of the linear regression equation you developed.Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home.ConclusionsSummarize findings: In one paragraph, summarize your findings in clear and concise plain language for the CEO to understand. Summarize your results.Did you see the results you expected, or was anything different from your expectations or experiences?What changes could support different results, or help to solve a different problem?Provide at least one question that would be interesting for follow-up research.You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics. The videos may use different national statistics. You should use the national statistics posted with this assignment.
University of Phoenix Chapter 7 Coronavirus and Americas Economy Article HW
Research an article on a current event that centers on a controversial issue where the two sides are claiming opposing vie ...
University of Phoenix Chapter 7 Coronavirus and Americas Economy Article HW
Research an article on a current event that centers on a controversial issue where the two sides are claiming opposing views. Then, describe how you would analyze the situation to settle the issue if you were involved in this event. For example, if the article was about whether a proposed new law about gun control will reduce deaths, you may describe how you would use hypothesis testing to compare data from states where such laws exist. Or, if the article was about actions to take to reduce gas prices, you could talk about how you would use regression to figure out which factors affected prices at the pump the most. General discussions like “should marijuana be legal” or “do vaccines cause autism” are not appropriate. Pick a current and specific debate.Please note that this discussion should be limited to how statistical analysis can be applied to current issues. This is not the place to champion a particular position on the issue you are discussing or get into an argument about the various sides of an issue. Remember, you are here to analyze, not proselytize.Also note that the article you are citing must be discussing the opposing views on the issue. Do not introduce your own perspective on what is being disputed. For example if the article is about the new budget being passed but does not discuss any conflicts of opinion, it doesn’t qualify.Please use the template below in your answers so everyone can easily follow your answers to all the questions (copy and paste to your post).Use this template for your Unit 6 Discussion.Summary of the articleBriefly describe the current event described in the article.Central questionWhat does the article say about the issue being disputed? What are the conflicting points of view according to the article? Use direct quotes from the article to summarize the dispute and the opposing sides.There has to be some specific issue in dispute at the center (do tax breaks increase spending, what impacts health care costs the most, etc.), and the sides have to be defending a particular position.Do not use examples where the issue is based on opinions or morality. For example, “Should abortion be legal?” is largely a morality question and is not suitable for statistical analysis. Conducting a survey to ask people about their opinions is not the same as analyzing data and making conclusions- you still only have opinions.MethodologyExplain which methodology you will apply. Provide the relevant details. Where will your data come from? How will the results from this methodology answer the question you described above?If you are going to use forecasting, explain how you will do that (which methodology and why) and how you will measure your accuracy. How will the forecast settle the issue?If you do a regression analysis, explain what the dependent and independent variables will be.If you will do hypothesis testing, what will the null and alternative hypothesis be?
Harvard University Practice Patterns of Dr Jones and Smith Excel Project
Question A: In the following question analyze the data.Assume that we have followed two clinicians, Smith and Jones, and c ...
Harvard University Practice Patterns of Dr Jones and Smith Excel Project
Question A: In the following question analyze the data.Assume that we have followed two clinicians, Smith and Jones, and constructed the decision trees in Figure 1.
Use the followingdata
Figure 1:Practice Patterns of Dr. Jones and Smith
1.What is the expected length of stay for each of the clinicians?
2.What is the expected length of stay for Dr. Smith if he were to take care of patients of Dr. Jones?
3.What is the expected length of stay for Dr. Jones if he were to take of patients of Dr. Smith?
Question B: The following data report length of stay (LOS) for 10 patients of Dr. Jones and 10 patients of Dr. Smith. What is the expected outcome (average outcome) for Dr. Smith? What is the expected outcomes if Dr. Jones if he was seeing Dr. Smith's patients? To answer this question, replace each outcome of Dr. Jones with average outcome of same type of patient seen by Dr. Smith. Is Dr. Smith more efficient than Dr. Jones?
Dr. Smith
Patient
Previous MI
CHF
Shock
LOS
1
1
1
0
4
2
1
1
0
5
3
1
0
0
4
4
1
0
1
5
5
1
0
1
4
6
1
0
1
4
7
1
0
1
5
8
0
0
0
2
9
0
0
0
2
10
0
0
0
1
Dr. Jones
Patient
Previous MI
CHF
Shock
LOS
1
1
1
0
5
2
1
1
0
5
3
1
1
0
5
4
1
1
1
5
5
1
0
1
5
6
1
0
1
5
7
1
0
1
5
8
1
0
0
4
9
0
0
0
2
10
0
0
0
2
Question C: In data presented in question B, what is the expected outcome if Dr. Smith sees patients of Dr. Jones?Note that Dr. Smith does not see any patient like patient 4 of Dr. Jones.We need to estimate a synthetic control for this patient.To do so, filter the data for patients of Dr. Smith (this is already done since the data of Dr. Smith is presented separately).Regress length of stay on previous MI, CHF, and Shock.You learned about regression in the first part of this course. Evaluate the regression equation at values corresponding to the condition of patient 8 of Dr. Jones.Use the regression prediction of length of stay to create a synthetic patient for Dr. Smith and calculate the expected outcome for Dr. Smith seeing patients of Dr. Jones.
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Statistics Question
I need help with the uploaded questions, I need answers to the questions and will like precise and straight forward answer ...
Statistics Question
I need help with the uploaded questions, I need answers to the questions and will like precise and straight forward answers. I will be submitting in 2days
ITEC 8437 WU Inferential Statistics One Sample T Test Male Professors Age Essay
A t test examines if two means (averages) are reliably different from each other; that is, whether any significant differe ...
ITEC 8437 WU Inferential Statistics One Sample T Test Male Professors Age Essay
A t test examines if two means (averages) are reliably different from each other; that is, whether any significant differences exist between the means of samples from different populations. For example, to what extent is the output of a local office which applied an IT solution different than the output of other local offices which did not apply the IT solution? Also, if you wanted to test whether the average IQ score of a group of students differs from 100, you may use a t test. A t test does more than just compare means; as an inferential statistic, t tests allow researchers to make inferences about the populations beyond their sample data.For this Assignment, you will use the IT Security database and conduct two t tests: (a) one-sample t test and (b) paired-samples t test and prepare an APA results write-up for each test....thank you
UC San Diego Management 3: Quantitative Methods in Business
The questions are attched This is a simulation exercise in R. you’ll be creating simulated data in this exercise
UC San Diego Management 3: Quantitative Methods in Business
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Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for ...
Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the housing prices based square footage. To complete this task, use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided.DirectionsUsing the Project One Template located in the What to Submit section, generate a report including your tables and graphs to determine if the square footage of a house is a good indicator for what the listing price should be. Reference the National Statistics and Graphs document for national comparisons and the Real Estate Data spreadsheet (both found in the Supporting Materials section) for your statistical analysis.Note: Present your data in a clearly labeled table and using clearly labeled graphs.Specifically, include the following in your report:IntroductionDescribe the report: Give a brief description of the purpose of your report.Define the question your report is trying to answer.Explain when using linear regression is most appropriate.When using linear regression, what would you expect the scatterplot to look like?Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.Data CollectionSampling the data: Select a random sample of 50 houses.Identify your response and predictor variables.Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model.Data AnalysisHistogram: For your two variables, create histograms.Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.Interpret the graphs and statistics:Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables.Compare and contrast the shape, center, spread, and any unusual characteristic for your sample of house sales with the national population. Is your sample representative of national housing market sales?Develop Your Regression ModelScatterplot: Provide a graph of the scatterplot of the data with a line of best fit.Explain if a regression model is appropriate to develop based on your scatterplot.Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.Identify any possible outliers or influential points and discuss their effect on the correlation.Discuss keeping or removing outlier data points and what impact your decision would have on your model.Find r: Find the correlation coefficient (r).Explain how the r value you calculated supports what you noticed in your scatterplot.Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables.Interpret regression equation: Interpret the slope and intercept in context.Strength of the equation: Provide and interpret R-squared.Determine the strength of the linear regression equation you developed.Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home.ConclusionsSummarize findings: In one paragraph, summarize your findings in clear and concise plain language for the CEO to understand. Summarize your results.Did you see the results you expected, or was anything different from your expectations or experiences?What changes could support different results, or help to solve a different problem?Provide at least one question that would be interesting for follow-up research.You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics. The videos may use different national statistics. You should use the national statistics posted with this assignment.
University of Phoenix Chapter 7 Coronavirus and Americas Economy Article HW
Research an article on a current event that centers on a controversial issue where the two sides are claiming opposing vie ...
University of Phoenix Chapter 7 Coronavirus and Americas Economy Article HW
Research an article on a current event that centers on a controversial issue where the two sides are claiming opposing views. Then, describe how you would analyze the situation to settle the issue if you were involved in this event. For example, if the article was about whether a proposed new law about gun control will reduce deaths, you may describe how you would use hypothesis testing to compare data from states where such laws exist. Or, if the article was about actions to take to reduce gas prices, you could talk about how you would use regression to figure out which factors affected prices at the pump the most. General discussions like “should marijuana be legal” or “do vaccines cause autism” are not appropriate. Pick a current and specific debate.Please note that this discussion should be limited to how statistical analysis can be applied to current issues. This is not the place to champion a particular position on the issue you are discussing or get into an argument about the various sides of an issue. Remember, you are here to analyze, not proselytize.Also note that the article you are citing must be discussing the opposing views on the issue. Do not introduce your own perspective on what is being disputed. For example if the article is about the new budget being passed but does not discuss any conflicts of opinion, it doesn’t qualify.Please use the template below in your answers so everyone can easily follow your answers to all the questions (copy and paste to your post).Use this template for your Unit 6 Discussion.Summary of the articleBriefly describe the current event described in the article.Central questionWhat does the article say about the issue being disputed? What are the conflicting points of view according to the article? Use direct quotes from the article to summarize the dispute and the opposing sides.There has to be some specific issue in dispute at the center (do tax breaks increase spending, what impacts health care costs the most, etc.), and the sides have to be defending a particular position.Do not use examples where the issue is based on opinions or morality. For example, “Should abortion be legal?” is largely a morality question and is not suitable for statistical analysis. Conducting a survey to ask people about their opinions is not the same as analyzing data and making conclusions- you still only have opinions.MethodologyExplain which methodology you will apply. Provide the relevant details. Where will your data come from? How will the results from this methodology answer the question you described above?If you are going to use forecasting, explain how you will do that (which methodology and why) and how you will measure your accuracy. How will the forecast settle the issue?If you do a regression analysis, explain what the dependent and independent variables will be.If you will do hypothesis testing, what will the null and alternative hypothesis be?
Harvard University Practice Patterns of Dr Jones and Smith Excel Project
Question A: In the following question analyze the data.Assume that we have followed two clinicians, Smith and Jones, and c ...
Harvard University Practice Patterns of Dr Jones and Smith Excel Project
Question A: In the following question analyze the data.Assume that we have followed two clinicians, Smith and Jones, and constructed the decision trees in Figure 1.
Use the followingdata
Figure 1:Practice Patterns of Dr. Jones and Smith
1.What is the expected length of stay for each of the clinicians?
2.What is the expected length of stay for Dr. Smith if he were to take care of patients of Dr. Jones?
3.What is the expected length of stay for Dr. Jones if he were to take of patients of Dr. Smith?
Question B: The following data report length of stay (LOS) for 10 patients of Dr. Jones and 10 patients of Dr. Smith. What is the expected outcome (average outcome) for Dr. Smith? What is the expected outcomes if Dr. Jones if he was seeing Dr. Smith's patients? To answer this question, replace each outcome of Dr. Jones with average outcome of same type of patient seen by Dr. Smith. Is Dr. Smith more efficient than Dr. Jones?
Dr. Smith
Patient
Previous MI
CHF
Shock
LOS
1
1
1
0
4
2
1
1
0
5
3
1
0
0
4
4
1
0
1
5
5
1
0
1
4
6
1
0
1
4
7
1
0
1
5
8
0
0
0
2
9
0
0
0
2
10
0
0
0
1
Dr. Jones
Patient
Previous MI
CHF
Shock
LOS
1
1
1
0
5
2
1
1
0
5
3
1
1
0
5
4
1
1
1
5
5
1
0
1
5
6
1
0
1
5
7
1
0
1
5
8
1
0
0
4
9
0
0
0
2
10
0
0
0
2
Question C: In data presented in question B, what is the expected outcome if Dr. Smith sees patients of Dr. Jones?Note that Dr. Smith does not see any patient like patient 4 of Dr. Jones.We need to estimate a synthetic control for this patient.To do so, filter the data for patients of Dr. Smith (this is already done since the data of Dr. Smith is presented separately).Regress length of stay on previous MI, CHF, and Shock.You learned about regression in the first part of this course. Evaluate the regression equation at values corresponding to the condition of patient 8 of Dr. Jones.Use the regression prediction of length of stay to create a synthetic patient for Dr. Smith and calculate the expected outcome for Dr. Smith seeing patients of Dr. Jones.
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