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here we have:
first triangle:
b = sqrt(25+25) = sqrt(50) = 5*sqrt(2)
second triangle:
since it is:
8 = (sqrt(3)/2) * 2a,
then I get:
a = 8/sqrt(3) = (8/3) * sqrt(3)
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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
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To prepare for this Discussion: Review Chapters 6 and 7 of the Frankfort-Nachmias & Leon-Guerrero text and in Chapter 7, p. 188, consider Hispanic migration and earnings and focus on how different levels of confidence and sample size work together.Review Magnusson’s web blog found in the Learning Resources to further your visualization and understanding of confidence intervals.Use the Course Guide and Assignment Help found in this week’s Learning Resources to search for a quantitative article related to confidence intervals.Using the SPSS software, General Social Survey dataset and choose a quantitative variable that interests you. By Day 3 Using SPSS: Take a random sample of 100.Calculate the 95% confidence interval for the variable.Calculate a 90% confidence interval.Take another random sample of 400.Calculate the 95% confidence interval for the variable.Calculate a 90% confidence interval. Post your results, the mean of Age to verify the dataset you used, and an explanation of how different levels of confidence and sample size affect the width of the confidence interval. Next, consider the statement, “Confidence intervals are underutilized” and explain what the implications might be of using or not using confidence intervals. Provide examples based on the results of your data. Also, use your research to support your findings.
GWU Hill Running Regression Worksheet
data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races ta ...
GWU Hill Running Regression Worksheet
data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races take place at various times of year throughout Scotland. The data set (scottish_hill_races.csv) posted on Blackboard contains recent information from 90 races regarding Distance (in kilometers), Climb (in meters), Time (record time in minutes), and Sex (1 for women and 0 for men).a) Find the equation of the estimated simple linear regression function that predicts Time based on Distance.b) Plot the data with regression function found in part a). Distinguish between data points for Women and data points for Men and include a key (legend).c) Now fit the first-order regression model that predicts Time based on Distance and Sex. Provide the equation.d) Plot Time against Distance with the two separate regression functions based on Sex (one for Women and one for Men). You also need to include the equations of the two regression functions.e) Find the joint confidence intervals for the slopes with a family (Bonferroni adjusted) confidence level of 98%. Include an interpretation of each.f) Test whether Sex should be dropped from the model while Distance is retained. Include the hypotheses, test-statistic, p-value, and conclusions.g) Finally, let us consider the model that predicts Time based on Distance and Sex with interaction. Provide the equation.h) Now test whether Sex should be dropped from the model while Distance and the interaction term are retained. Include the hypotheses, test-statistic, p-value, and conclusions.i) Report the final model with Sex dropped. Does this improve upon the model found in part d)? Explain.2. Continue with the data set scottish_hill_races.csv.a) Fit the first-order regression model that predicts Time based on all potential predictors- Distance Climb, and Sex. Provide the equation.b) Construct a 95% prediction interval for the time it takes a woman to complete a 10 km race with a “climb” of 500 meters.c) Perform an exhaustive search for the “best” subsets of predictors. Which model was chosen as “best” for one predictor? Was it the one we examined in #1? How about for the “best” model with two predictors? Is it the one we examined in #1?d) Examine important criteria for the three “best” models chosen in c). Which model(s) should be included for final consideration based on them?e) Use forward stepwise selection with partial 𝐹-tests and α-to-enter= 0.01. Then use backward stepwise selection with partial 𝐹-tests and α-to-remove= 0.01. Which model is chosen as “best” in each case?f) Considering all results, which model(s) should be considered? Assess the predictive ability of the model(s) by splitting the data into training and testing (sample size 𝑛 = 40) subsets and estimating the mean squared prediction error 𝑀𝑆𝑃𝐸.g) Is there any indication of nonlinear relationships between Time and any of the quantitative predictors? Explain.h) Using basic diagnostics, is there any evidence of multicollinearity?i) Find the variance inflation factors for the quantitative predictors. Explain
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Most Popular Content
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?
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To prepare for this Discussion: Review Chapters 6 and 7 of the Frankfort-Nachmias & Leon-Guerrero text and in Chapter 7, p. 188, consider Hispanic migration and earnings and focus on how different levels of confidence and sample size work together.Review Magnusson’s web blog found in the Learning Resources to further your visualization and understanding of confidence intervals.Use the Course Guide and Assignment Help found in this week’s Learning Resources to search for a quantitative article related to confidence intervals.Using the SPSS software, General Social Survey dataset and choose a quantitative variable that interests you. By Day 3 Using SPSS: Take a random sample of 100.Calculate the 95% confidence interval for the variable.Calculate a 90% confidence interval.Take another random sample of 400.Calculate the 95% confidence interval for the variable.Calculate a 90% confidence interval. Post your results, the mean of Age to verify the dataset you used, and an explanation of how different levels of confidence and sample size affect the width of the confidence interval. Next, consider the statement, “Confidence intervals are underutilized” and explain what the implications might be of using or not using confidence intervals. Provide examples based on the results of your data. Also, use your research to support your findings.
GWU Hill Running Regression Worksheet
data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races ta ...
GWU Hill Running Regression Worksheet
data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races take place at various times of year throughout Scotland. The data set (scottish_hill_races.csv) posted on Blackboard contains recent information from 90 races regarding Distance (in kilometers), Climb (in meters), Time (record time in minutes), and Sex (1 for women and 0 for men).a) Find the equation of the estimated simple linear regression function that predicts Time based on Distance.b) Plot the data with regression function found in part a). Distinguish between data points for Women and data points for Men and include a key (legend).c) Now fit the first-order regression model that predicts Time based on Distance and Sex. Provide the equation.d) Plot Time against Distance with the two separate regression functions based on Sex (one for Women and one for Men). You also need to include the equations of the two regression functions.e) Find the joint confidence intervals for the slopes with a family (Bonferroni adjusted) confidence level of 98%. Include an interpretation of each.f) Test whether Sex should be dropped from the model while Distance is retained. Include the hypotheses, test-statistic, p-value, and conclusions.g) Finally, let us consider the model that predicts Time based on Distance and Sex with interaction. Provide the equation.h) Now test whether Sex should be dropped from the model while Distance and the interaction term are retained. Include the hypotheses, test-statistic, p-value, and conclusions.i) Report the final model with Sex dropped. Does this improve upon the model found in part d)? Explain.2. Continue with the data set scottish_hill_races.csv.a) Fit the first-order regression model that predicts Time based on all potential predictors- Distance Climb, and Sex. Provide the equation.b) Construct a 95% prediction interval for the time it takes a woman to complete a 10 km race with a “climb” of 500 meters.c) Perform an exhaustive search for the “best” subsets of predictors. Which model was chosen as “best” for one predictor? Was it the one we examined in #1? How about for the “best” model with two predictors? Is it the one we examined in #1?d) Examine important criteria for the three “best” models chosen in c). Which model(s) should be included for final consideration based on them?e) Use forward stepwise selection with partial 𝐹-tests and α-to-enter= 0.01. Then use backward stepwise selection with partial 𝐹-tests and α-to-remove= 0.01. Which model is chosen as “best” in each case?f) Considering all results, which model(s) should be considered? Assess the predictive ability of the model(s) by splitting the data into training and testing (sample size 𝑛 = 40) subsets and estimating the mean squared prediction error 𝑀𝑆𝑃𝐸.g) Is there any indication of nonlinear relationships between Time and any of the quantitative predictors? Explain.h) Using basic diagnostics, is there any evidence of multicollinearity?i) Find the variance inflation factors for the quantitative predictors. Explain
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Complete the following questions. (PLEASE WRITE ANSWERS IN A WORD DOCUMENT!!) --LINK-- http://ogburn.org/wp-content/upload ...
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Complete the following questions. (PLEASE WRITE ANSWERS IN A WORD DOCUMENT!!) --LINK-- http://ogburn.org/wp-content/uploads/2016/05/Alg-I...
10 pages
20160129192837math301week1homework Answers
Instructions: You are encouraged to discuss homework, consult (but not plagiarize) online resources, and to seek help from ...
20160129192837math301week1homework Answers
Instructions: You are encouraged to discuss homework, consult (but not plagiarize) online resources, and to seek help from the instructor when you ...
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