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Statistics and Probability, algebra homework help
Complete the following questions. (PLEASE WRITE ANSWERS IN A WORD DOCUMENT!!!) --LINK-- http://ogburn.org/wp-content/uploa ...
Statistics and Probability, algebra homework help
Complete the following questions. (PLEASE WRITE ANSWERS IN A WORD DOCUMENT!!!) --LINK-- http://ogburn.org/wp-content/uploads/2016/05/Alg-I...
Res 710 discussion posts
PART 1. Frankfort-Nachmias and Leon-Guerrero (2018) noted that the precision of a confidence interval can be enhanced by ...
Res 710 discussion posts
PART 1. Frankfort-Nachmias and Leon-Guerrero (2018) noted that the precision of a confidence interval can be enhanced by increasing the sample size. Write a 250- to 300-word response to the following: What is the role of sample size in the calculation of confidence intervals? What factors might determine the size of an ideal sample in your dissertation study? Reference: Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: SAGE Publications, Inc. PART 2. Reply in 150 or more words Here is something I learned recently. I had a student who used a second party data collection cite. He received the data and sample size he needed but most of the data was filled out as all zeros or all 10s as the participant did not actually take the survey and just filled it out quickly. Do you think this data should count and what can we do if this occurs? PART 3 Write a 250- to 300-word response to the following: How can estimation errors threaten the validity of a study? Cite specific examples from your experience to support your response. PART 4 Reply In at least 150 words. When we look at estimating errors, this can be a key reflection of the validity of the sample data. For example, as systematic estimation errors increase validity decreases. Likewise, as systematic estimation errors decrease, validity increases. Why do you think that is?
MAT 243 Southern New Hampshire University Statistical Analysis Projects Report
Use the link in the Jupyter Notebook activity to access your Python script. Once you have made your calculations, complete ...
MAT 243 Southern New Hampshire University Statistical Analysis Projects Report
Use the link in the Jupyter Notebook activity to access your Python script. Once you have made your calculations, complete this discussion. The script will output answers to the questions given below. You must attach your Python script output as an HTML file and respond to the questions below.In this discussion, you will apply the statistical concepts and techniques covered in this week's reading to calculate a confidence interval and perform hypothesis testing for a manufacturing process.The manufacturing process at a factory produces ball bearings that are sold to automotive manufacturers. The factory wants to estimate the average diameter of a ball bearing that is in demand to ensure that it is manufactured within the specifications. Suppose they plan to collect a sample of 50 ball bearings and measure their diameters to construct a 90% and 99% confidence interval for the average diameter of ball bearings produced from this manufacturing process.The sample of size 50 was generated using Python’s numpy module. This data set will be unique to you, and therefore your answers will be unique as well. Run Step 1 in the Python script to generate your unique sample data. Check to make sure your sample data is shown in your attachment.In your initial post, address the following items. Be sure to answer the questions about both confidence intervals and hypothesis testing.In the Python script, you calculated the sample data to construct a 90% and 99% confidence interval for the average diameter of ball bearings produced from this manufacturing process. These confidence intervals were created using the Normal distribution based on the assumption that the population standard deviation is known and the sample size is sufficiently large. Report these confidence intervals rounded to two decimal places. See Step 2 in the Python script.Interpret both confidence intervals. Make sure to be detailed and precise in your interpretation.It has been claimed from previous studies that the average diameter of ball bearings from this manufacturing process is 2.30 cm. Based on the sample of 50 that you collected, is there evidence to suggest that the average diameter is greater than 2.30 cm? Perform a hypothesis test for the population mean at alpha = 0.01.In your initial post, address the following items:Define the null and alternative hypothesis for this test in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 3 in the Python script. (Note that Python methods return two tailed P-values. You must report the correct P-value based on the alternative hypothesis.)Provide your conclusion and interpretation of the results. Should the null hypothesis be rejected? Why or why not?In your follow-up posts to other students, review your peers' calculations and provide some analysis and interpretation:How do their confidence intervals compare with yours?If the population standard deviation is unknown and the sample size is not sufficiently large, would you still use the Normal distribution to calculate these confidence intervals, or would you choose another distribution? If the latter, which distribution would you choose?Remember to attach your Python output and respond to all questions in your initial and follow-up posts. Be sure to clearly communicate your ideas using appropriate terminology. Finally, be sure to review the Discussion Rubric to understand how you will be graded on this assignment.PART 2 :ScenarioYou are a data analyst for a basketball team. You have found a large set of historical data, and are working to analyze and find patterns in the data set. The coach of the team and your management have requested that you use descriptive statistics and data visualization techniques to study distributions of key variables associated with the performance of different teams. Data-driven analytics will help the management make decisions to further improve your team’s performance. You will use the Python programming language to perform your statistical analysis. You will also need to present a report of your findings to the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications. The managers will use your report to find areas where the team can improve its performance.Note: This data set has been “cleaned” for the purposes of this assignment.ReferenceFiveThirtyEight. (April 26, 2019). FiveThirtyEight NBA Elo dataset. Kaggle. Retrieved from https://www.kaggle.com/fivethirtyeight/fivethirtye...DirectionsFor this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.Python Script: To complete the tasks listed below, open the Project One Jupyter Notebook link in the Assignment Information module. Your project contains the NBA data set and a Jupyter Notebook with your Python scripts. In the notebook, you will find step-by-step instructions and code blocks that will help you complete the following tasks:Choose and create a data visualization.Calculate descriptive statistics including mean, median, min, max, variance, and standard deviation.Construct confidence intervals for a population proportion and a population mean.Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:Introduction: Set the context for your scenario and the analyses you will be performing.Data Visualization: Identify and interpret your chosen data visualization.Descriptive Statistics: Identify and interpret measures of central tendency and variability.Confidence Intervals: Identify and interpret the lower and upper limits of confidence intervals.Conclusion: Summarize your findings and explain their practical implications.What to SubmitTo complete this project, you must submit the following:Python ScriptYour Jupyter Notebook Python script contains all the statistical analyses you completed for this project. You downloaded your work as an HTML file. Review the file to make sure that every step and all your outputs are included. Submit the HTML file as part of your submission. Review the Jupyter Notebook in Codio Tutorial in the Supporting Materials section if you need help.Summary ReportUse the provided template to create your summary report. The template contains guiding questions to help you complete each section. Be sure to remove these questions before submitting your report. Your summary report should be submitted as a 3- to 5-page Microsoft Word document. It should include an APA-style cover page and APA citations for any sources used. Use double spacing, 12-point Times New Roman font, and one-inch margins.Supporting MaterialsThe following resource(s) may help support your work on the project:Document: Jupyter Notebook in Codio TutorialThis tutorial will help you become familiar with the Jupyter Notebook interface. You will learn how to open, complete, save, and download your Jupyter Notebook for this project.Shapiro Library: APA Style GuideThis guide will help you format your cover page and references according to APA style. You are not required to use external resources for this project. However, if you do use any resources, you must cite them in APA format.
MATH 107 University of Maryland University College Algebra Linear Project Worksheet
Choose an Olympic sport -- an event that interests you. Make a quick plot for yourself to "eyeball" whether the data point ...
MATH 107 University of Maryland University College Algebra Linear Project Worksheet
Choose an Olympic sport -- an event that interests you. Make a quick plot for yourself to "eyeball" whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different event.) After you find the line of best fit, use your line to make a prediction for the next 2 Olympics
(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data points. Label appropriately. (Highly recommended: Post this information in the Linear Model Project discussion as well as in your completed project. Include a brief informative description in the title of your posting. Each student must use different data.)
(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different topic or data set.)
(LR-3) Find the line of best fit (regression line) and graph it on the scatterplot.
(LR-4) State the equation of the line. State the slope of the line of best fit. Carefully interpret the meaning of the slope in a sentence or two.
(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?
(LR-6) Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.
(LR-7) Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting.
Discussion
As a marketing analyst, you are responsible for estimating the level of sales associated with different marketing mix allo ...
Discussion
As a marketing analyst, you are responsible for estimating the level of sales associated with different marketing mix allocation scenarios. You have historical sales data, as well as promotional response data, for each of the elements of the marketing mix.Describe the differences between the forecasting methods that can be used.Evaluate the forecasting methods in relation to the given scenario.Choose a forecasting method and justify your choice. If you make any assumptions, state them explicitly. Support your discussion with relevant examples, research, and rationale.500 words
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Statistics and Probability, algebra homework help
Complete the following questions. (PLEASE WRITE ANSWERS IN A WORD DOCUMENT!!!) --LINK-- http://ogburn.org/wp-content/uploa ...
Statistics and Probability, algebra homework help
Complete the following questions. (PLEASE WRITE ANSWERS IN A WORD DOCUMENT!!!) --LINK-- http://ogburn.org/wp-content/uploads/2016/05/Alg-I...
Res 710 discussion posts
PART 1. Frankfort-Nachmias and Leon-Guerrero (2018) noted that the precision of a confidence interval can be enhanced by ...
Res 710 discussion posts
PART 1. Frankfort-Nachmias and Leon-Guerrero (2018) noted that the precision of a confidence interval can be enhanced by increasing the sample size. Write a 250- to 300-word response to the following: What is the role of sample size in the calculation of confidence intervals? What factors might determine the size of an ideal sample in your dissertation study? Reference: Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: SAGE Publications, Inc. PART 2. Reply in 150 or more words Here is something I learned recently. I had a student who used a second party data collection cite. He received the data and sample size he needed but most of the data was filled out as all zeros or all 10s as the participant did not actually take the survey and just filled it out quickly. Do you think this data should count and what can we do if this occurs? PART 3 Write a 250- to 300-word response to the following: How can estimation errors threaten the validity of a study? Cite specific examples from your experience to support your response. PART 4 Reply In at least 150 words. When we look at estimating errors, this can be a key reflection of the validity of the sample data. For example, as systematic estimation errors increase validity decreases. Likewise, as systematic estimation errors decrease, validity increases. Why do you think that is?
MAT 243 Southern New Hampshire University Statistical Analysis Projects Report
Use the link in the Jupyter Notebook activity to access your Python script. Once you have made your calculations, complete ...
MAT 243 Southern New Hampshire University Statistical Analysis Projects Report
Use the link in the Jupyter Notebook activity to access your Python script. Once you have made your calculations, complete this discussion. The script will output answers to the questions given below. You must attach your Python script output as an HTML file and respond to the questions below.In this discussion, you will apply the statistical concepts and techniques covered in this week's reading to calculate a confidence interval and perform hypothesis testing for a manufacturing process.The manufacturing process at a factory produces ball bearings that are sold to automotive manufacturers. The factory wants to estimate the average diameter of a ball bearing that is in demand to ensure that it is manufactured within the specifications. Suppose they plan to collect a sample of 50 ball bearings and measure their diameters to construct a 90% and 99% confidence interval for the average diameter of ball bearings produced from this manufacturing process.The sample of size 50 was generated using Python’s numpy module. This data set will be unique to you, and therefore your answers will be unique as well. Run Step 1 in the Python script to generate your unique sample data. Check to make sure your sample data is shown in your attachment.In your initial post, address the following items. Be sure to answer the questions about both confidence intervals and hypothesis testing.In the Python script, you calculated the sample data to construct a 90% and 99% confidence interval for the average diameter of ball bearings produced from this manufacturing process. These confidence intervals were created using the Normal distribution based on the assumption that the population standard deviation is known and the sample size is sufficiently large. Report these confidence intervals rounded to two decimal places. See Step 2 in the Python script.Interpret both confidence intervals. Make sure to be detailed and precise in your interpretation.It has been claimed from previous studies that the average diameter of ball bearings from this manufacturing process is 2.30 cm. Based on the sample of 50 that you collected, is there evidence to suggest that the average diameter is greater than 2.30 cm? Perform a hypothesis test for the population mean at alpha = 0.01.In your initial post, address the following items:Define the null and alternative hypothesis for this test in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 3 in the Python script. (Note that Python methods return two tailed P-values. You must report the correct P-value based on the alternative hypothesis.)Provide your conclusion and interpretation of the results. Should the null hypothesis be rejected? Why or why not?In your follow-up posts to other students, review your peers' calculations and provide some analysis and interpretation:How do their confidence intervals compare with yours?If the population standard deviation is unknown and the sample size is not sufficiently large, would you still use the Normal distribution to calculate these confidence intervals, or would you choose another distribution? If the latter, which distribution would you choose?Remember to attach your Python output and respond to all questions in your initial and follow-up posts. Be sure to clearly communicate your ideas using appropriate terminology. Finally, be sure to review the Discussion Rubric to understand how you will be graded on this assignment.PART 2 :ScenarioYou are a data analyst for a basketball team. You have found a large set of historical data, and are working to analyze and find patterns in the data set. The coach of the team and your management have requested that you use descriptive statistics and data visualization techniques to study distributions of key variables associated with the performance of different teams. Data-driven analytics will help the management make decisions to further improve your team’s performance. You will use the Python programming language to perform your statistical analysis. You will also need to present a report of your findings to the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications. The managers will use your report to find areas where the team can improve its performance.Note: This data set has been “cleaned” for the purposes of this assignment.ReferenceFiveThirtyEight. (April 26, 2019). FiveThirtyEight NBA Elo dataset. Kaggle. Retrieved from https://www.kaggle.com/fivethirtyeight/fivethirtye...DirectionsFor this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.Python Script: To complete the tasks listed below, open the Project One Jupyter Notebook link in the Assignment Information module. Your project contains the NBA data set and a Jupyter Notebook with your Python scripts. In the notebook, you will find step-by-step instructions and code blocks that will help you complete the following tasks:Choose and create a data visualization.Calculate descriptive statistics including mean, median, min, max, variance, and standard deviation.Construct confidence intervals for a population proportion and a population mean.Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:Introduction: Set the context for your scenario and the analyses you will be performing.Data Visualization: Identify and interpret your chosen data visualization.Descriptive Statistics: Identify and interpret measures of central tendency and variability.Confidence Intervals: Identify and interpret the lower and upper limits of confidence intervals.Conclusion: Summarize your findings and explain their practical implications.What to SubmitTo complete this project, you must submit the following:Python ScriptYour Jupyter Notebook Python script contains all the statistical analyses you completed for this project. You downloaded your work as an HTML file. Review the file to make sure that every step and all your outputs are included. Submit the HTML file as part of your submission. Review the Jupyter Notebook in Codio Tutorial in the Supporting Materials section if you need help.Summary ReportUse the provided template to create your summary report. The template contains guiding questions to help you complete each section. Be sure to remove these questions before submitting your report. Your summary report should be submitted as a 3- to 5-page Microsoft Word document. It should include an APA-style cover page and APA citations for any sources used. Use double spacing, 12-point Times New Roman font, and one-inch margins.Supporting MaterialsThe following resource(s) may help support your work on the project:Document: Jupyter Notebook in Codio TutorialThis tutorial will help you become familiar with the Jupyter Notebook interface. You will learn how to open, complete, save, and download your Jupyter Notebook for this project.Shapiro Library: APA Style GuideThis guide will help you format your cover page and references according to APA style. You are not required to use external resources for this project. However, if you do use any resources, you must cite them in APA format.
MATH 107 University of Maryland University College Algebra Linear Project Worksheet
Choose an Olympic sport -- an event that interests you. Make a quick plot for yourself to "eyeball" whether the data point ...
MATH 107 University of Maryland University College Algebra Linear Project Worksheet
Choose an Olympic sport -- an event that interests you. Make a quick plot for yourself to "eyeball" whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different event.) After you find the line of best fit, use your line to make a prediction for the next 2 Olympics
(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data points. Label appropriately. (Highly recommended: Post this information in the Linear Model Project discussion as well as in your completed project. Include a brief informative description in the title of your posting. Each student must use different data.)
(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different topic or data set.)
(LR-3) Find the line of best fit (regression line) and graph it on the scatterplot.
(LR-4) State the equation of the line. State the slope of the line of best fit. Carefully interpret the meaning of the slope in a sentence or two.
(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?
(LR-6) Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.
(LR-7) Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting.
Discussion
As a marketing analyst, you are responsible for estimating the level of sales associated with different marketing mix allo ...
Discussion
As a marketing analyst, you are responsible for estimating the level of sales associated with different marketing mix allocation scenarios. You have historical sales data, as well as promotional response data, for each of the elements of the marketing mix.Describe the differences between the forecasting methods that can be used.Evaluate the forecasting methods in relation to the given scenario.Choose a forecasting method and justify your choice. If you make any assumptions, state them explicitly. Support your discussion with relevant examples, research, and rationale.500 words
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