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Attachment 1 23
Questions 1 and 2: After doing some work in the house, Bob and Carol want to put a concrete patio on the side of the house ...
Attachment 1 23
Questions 1 and 2: After doing some work in the house, Bob and Carol want to put a concrete patio on the side of the house to keep people from ...
7 pages
Critical Thinking Discussion.edited
Recall the following critical thinking skills: Inference, Deduction, Induction, Analysis, and Evaluation. In mathematics, ...
Critical Thinking Discussion.edited
Recall the following critical thinking skills: Inference, Deduction, Induction, Analysis, and Evaluation. In mathematics, each of these skills are ...
MAT 144 Grand Canyon University Technology Question
For this DQ, you’ll complete a modified version of Technology Assignment 1 in Lesson 3-3 of the textbook in ALEKS, for w ...
MAT 144 Grand Canyon University Technology Question
For this DQ, you’ll complete a modified version of Technology Assignment 1 in Lesson 3-3 of the textbook in ALEKS, for which you’ll calculate the probabilities of various games of chance, using permutations (selection of items when the order matters) and combinations (selection of items when order does not matter).Download the attached template (“QR 3-3 Tech Template MODIFIED.xlsx”) and follow these steps (note that the ALEKS video for the template may not help that much):For each game described in column A, indicate in column B whether this involves permutations (selection of items where the order of selection matters) or combinations (where the order of selection does not matter). Enter either “Permutation” or “Combination”.In column C, provide a short description, based on the game information in column A, of the number of outcomes for the game (i.e., different possible ways in which the game could come out).In column D, use either the Excel PERMUT() function or the Excel COMBIN() function to calculate the number of outcomes for the game.In column E, describe what you would have to do to win this game.In column F, enter the number of ways in which you can win. Note that these will all be simple number entries except for the last game, which requires a bit more consideration; for that last game, see the hint in the text box below the table.In column G, calculate the probability of winning, which will be =(# of ways to win)/(total # of outcomes). You must use Excel formulas here.Finally, in column H, calculate the odds against winning, which is given by:(odds against) = (1 – probability of winning) / (probability of winning)The entries for the first game are filled in for you; feel free to use these as a model for your other entries.MAT-144 T5 DQ2 Explanation - YouTube
2 pages
Assignment Evaluating Significance Of Findings
The study aimed at examining the differences in student satisfaction between students in tradition and online classrooms. ...
Assignment Evaluating Significance Of Findings
The study aimed at examining the differences in student satisfaction between students in tradition and online classrooms. The study used a sample size ...
BADM 7020 LSU Mod 4 ABC Company Factors & Parameter Estimates for 4 Biggest Factors Paper
Module 4 AssignmentIn this assignment, you will apply what you've learned in this module about the designs of experiments ...
BADM 7020 LSU Mod 4 ABC Company Factors & Parameter Estimates for 4 Biggest Factors Paper
Module 4 AssignmentIn this assignment, you will apply what you've learned in this module about the designs of experiments to a sample data set and scenario.Assignment InstructionsConsider the following: The ABC Company wants to optimize the response (click rate) to their online ads. After a brainstorming session, thirteen factors were identified as potentially having an effect on the response (click) rate. The table below lists the 13 factors and the two levels that should be considered. This data is available in the DOE Assignment JMP file attached below. Identified Response FactorsTeaser OfferTelephoneNumberGraphicFont SizeAdvertisingChanelMessageTypeHeadlineLayoutProductselectionGift OfferProduc InfoColorSchemaDiscountNumber ofClicksLevel 1YesYesYesLargeYesAHeadline 1StandardFeature AYesVersion AAYesLevel 2NoNoNoSmallNoBHeadline 2CreativeFeature BNoVersion BBNo1YesYesYesLargeYesAHeadline 1StandardFeature AYesVersion AAYes522NoYesNoLargeYesBHeadline2CreativeFeature AYesVersion BANo383YesNoNoSmallYesBHeadline 1StandardFeature BYesVersion BBNo424YesYesYesSmallNoBHeadline 1CreativeFeature ANoVersion BBYes1345NoYesYesLargeNoBHeadline 1CreativeFeature BYesVersion BBYes1046NoNoNoLargeYesAHeadline 1CreativeFeature ANoVersion ABYes607NoNoYesSmallYesAHeadline 2CreativeFeature BYesVersion BAYes618NoNoYesLargeNoBHeadline 2StandardFeature BNoVersion ABNo689YesNoNoLargeYesBHeadline 1StandardFeature BNoVersion BAYes5710NoYesNoSmallYesAHeadline 1CreativeFeature BNoVersion ABNo3011YesNoNoSmallNoBHeadline 2CreativeFeature ANoVersion AAYes10812NoYesNoSmallNoBHeadline 1StandardFeature AYesVersion AANo3913YesNoYesSmallNoAHeadline 1CreativeFeature BYesVersion AANo4014YesYesNoLargeNoAHeadline 2CreativeFeature BNoVersion BANo4915YesYesYesSmallYesAHeadline 2StandardFeature ANoVersion BBNo3716YesYesNoLargeNoAHeadline 2StandardFeature BYesVersion ABYes9917NoYesYesSmallYesBHeadline 2StandardFeature BNoVersion AAYes8618NoNoYesLargeNoAHeadline 1StandardFeature ANoVersion BANo4319YesNoYesLargeYesBHeadline 2CreativeFeature AYesVersion ABNo4720NoNoNoSmallNoAHeadline 2StandardFeature AYesVersion BBYes104Discuss how you approach the problems and answer the questions along the way.1. How many treatments do you need at a minimum to estimate 13 main effects and the overall mean? Find a design using JMP DOE>Classical Designs>Screening Designs add 13 factors and find a design.What is the minimum number of treatments (runs)?What is the fractional factorial design with the smallest number of runs you can use for our problem?Which other design could you choose?2. Once you have a design matrix you would carry out the treatments and collect the response for each treatment (run). To exercise the analysis of a design I provided you with a 20 run design (which is the Packett-Burman design shown ion your list) which has responses provided in the JMP file. Use the design matrix provided in the DOE_Assignment_5_Click(2).jmp file with the number of clicks as the response variable. Use DOE>Classical>Two Level Screening> Fit Two Level Screening . Which factors are statistically significant at p<=0.05? Highlight the statistically significant factor rows (use individual p) and click run model. Interpret the output.
3. To evaluate the current design matrix with just the few main factors you determined to be significant, use DOE>Design Diagnostics>Evaluate Design. Select only the statistically significant factors for the evaluation. Look at the Alias Matrix to see what the problems are with using the same 20 runs to estimate the interaction effects (confounding of main effects and interaction effects). Specifically, we are interested in the 2-factor interaction between the biggest effects. What main factors are confounded with this interaction and what is the magnitude? Interpret the finding. (Note: find the column of the 2-factor interaction which had the largest effect. Then see what row has a number different from zero and what the main effect in that row is. The larger the absolute value the larger is the confounding. )4. Now we want to evaluate the data based on our discovery that the 2-factor interaction is confounded with another important factor. Go back to the open window you had before (DOE>Classical>Two Level Screening> Fit Two Level Screening ) and select the statistically significant factors plus the 2-factor interaction of the two biggest effects. Click Run Model again. Interpret the output. What is likely happening?5. Make a final selection on the window (DOE>Classical>Two Level Screening> Fit Two Level Screening) of what you think is the true likely factors and or interactions. Then click Run Model again. Interpret final model. Prepare the report using the following formatting guidelines:1 page, single-spaced report using 0.5 margins and two-column format1 page for appendixInclude title of report, then FirstName, LastName, ISDS course #, Assignment #, date (00/00/00)10 pt Font Calibri or Times New RomanJustified as sample reportCreate headings for each sectionList any references used (e.g. Module 1 Resources)Include a title for your report e.g. "Text Analysis of Workers Compensation Claims" and create headings for each sectionInclude supporting relevant figures from the analysis in your AppendixSubmit as pdf with filename first name initial last name and assignment number (for instance HSchneider#1)Be sure to review the Assignment Rubric and Assignment Example attached below. If you have any questions, please post in the Module Questions Forum.
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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4 pages
Attachment 1 23
Questions 1 and 2: After doing some work in the house, Bob and Carol want to put a concrete patio on the side of the house ...
Attachment 1 23
Questions 1 and 2: After doing some work in the house, Bob and Carol want to put a concrete patio on the side of the house to keep people from ...
7 pages
Critical Thinking Discussion.edited
Recall the following critical thinking skills: Inference, Deduction, Induction, Analysis, and Evaluation. In mathematics, ...
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Recall the following critical thinking skills: Inference, Deduction, Induction, Analysis, and Evaluation. In mathematics, each of these skills are ...
MAT 144 Grand Canyon University Technology Question
For this DQ, you’ll complete a modified version of Technology Assignment 1 in Lesson 3-3 of the textbook in ALEKS, for w ...
MAT 144 Grand Canyon University Technology Question
For this DQ, you’ll complete a modified version of Technology Assignment 1 in Lesson 3-3 of the textbook in ALEKS, for which you’ll calculate the probabilities of various games of chance, using permutations (selection of items when the order matters) and combinations (selection of items when order does not matter).Download the attached template (“QR 3-3 Tech Template MODIFIED.xlsx”) and follow these steps (note that the ALEKS video for the template may not help that much):For each game described in column A, indicate in column B whether this involves permutations (selection of items where the order of selection matters) or combinations (where the order of selection does not matter). Enter either “Permutation” or “Combination”.In column C, provide a short description, based on the game information in column A, of the number of outcomes for the game (i.e., different possible ways in which the game could come out).In column D, use either the Excel PERMUT() function or the Excel COMBIN() function to calculate the number of outcomes for the game.In column E, describe what you would have to do to win this game.In column F, enter the number of ways in which you can win. Note that these will all be simple number entries except for the last game, which requires a bit more consideration; for that last game, see the hint in the text box below the table.In column G, calculate the probability of winning, which will be =(# of ways to win)/(total # of outcomes). You must use Excel formulas here.Finally, in column H, calculate the odds against winning, which is given by:(odds against) = (1 – probability of winning) / (probability of winning)The entries for the first game are filled in for you; feel free to use these as a model for your other entries.MAT-144 T5 DQ2 Explanation - YouTube
2 pages
Assignment Evaluating Significance Of Findings
The study aimed at examining the differences in student satisfaction between students in tradition and online classrooms. ...
Assignment Evaluating Significance Of Findings
The study aimed at examining the differences in student satisfaction between students in tradition and online classrooms. The study used a sample size ...
BADM 7020 LSU Mod 4 ABC Company Factors & Parameter Estimates for 4 Biggest Factors Paper
Module 4 AssignmentIn this assignment, you will apply what you've learned in this module about the designs of experiments ...
BADM 7020 LSU Mod 4 ABC Company Factors & Parameter Estimates for 4 Biggest Factors Paper
Module 4 AssignmentIn this assignment, you will apply what you've learned in this module about the designs of experiments to a sample data set and scenario.Assignment InstructionsConsider the following: The ABC Company wants to optimize the response (click rate) to their online ads. After a brainstorming session, thirteen factors were identified as potentially having an effect on the response (click) rate. The table below lists the 13 factors and the two levels that should be considered. This data is available in the DOE Assignment JMP file attached below. Identified Response FactorsTeaser OfferTelephoneNumberGraphicFont SizeAdvertisingChanelMessageTypeHeadlineLayoutProductselectionGift OfferProduc InfoColorSchemaDiscountNumber ofClicksLevel 1YesYesYesLargeYesAHeadline 1StandardFeature AYesVersion AAYesLevel 2NoNoNoSmallNoBHeadline 2CreativeFeature BNoVersion BBNo1YesYesYesLargeYesAHeadline 1StandardFeature AYesVersion AAYes522NoYesNoLargeYesBHeadline2CreativeFeature AYesVersion BANo383YesNoNoSmallYesBHeadline 1StandardFeature BYesVersion BBNo424YesYesYesSmallNoBHeadline 1CreativeFeature ANoVersion BBYes1345NoYesYesLargeNoBHeadline 1CreativeFeature BYesVersion BBYes1046NoNoNoLargeYesAHeadline 1CreativeFeature ANoVersion ABYes607NoNoYesSmallYesAHeadline 2CreativeFeature BYesVersion BAYes618NoNoYesLargeNoBHeadline 2StandardFeature BNoVersion ABNo689YesNoNoLargeYesBHeadline 1StandardFeature BNoVersion BAYes5710NoYesNoSmallYesAHeadline 1CreativeFeature BNoVersion ABNo3011YesNoNoSmallNoBHeadline 2CreativeFeature ANoVersion AAYes10812NoYesNoSmallNoBHeadline 1StandardFeature AYesVersion AANo3913YesNoYesSmallNoAHeadline 1CreativeFeature BYesVersion AANo4014YesYesNoLargeNoAHeadline 2CreativeFeature BNoVersion BANo4915YesYesYesSmallYesAHeadline 2StandardFeature ANoVersion BBNo3716YesYesNoLargeNoAHeadline 2StandardFeature BYesVersion ABYes9917NoYesYesSmallYesBHeadline 2StandardFeature BNoVersion AAYes8618NoNoYesLargeNoAHeadline 1StandardFeature ANoVersion BANo4319YesNoYesLargeYesBHeadline 2CreativeFeature AYesVersion ABNo4720NoNoNoSmallNoAHeadline 2StandardFeature AYesVersion BBYes104Discuss how you approach the problems and answer the questions along the way.1. How many treatments do you need at a minimum to estimate 13 main effects and the overall mean? Find a design using JMP DOE>Classical Designs>Screening Designs add 13 factors and find a design.What is the minimum number of treatments (runs)?What is the fractional factorial design with the smallest number of runs you can use for our problem?Which other design could you choose?2. Once you have a design matrix you would carry out the treatments and collect the response for each treatment (run). To exercise the analysis of a design I provided you with a 20 run design (which is the Packett-Burman design shown ion your list) which has responses provided in the JMP file. Use the design matrix provided in the DOE_Assignment_5_Click(2).jmp file with the number of clicks as the response variable. Use DOE>Classical>Two Level Screening> Fit Two Level Screening . Which factors are statistically significant at p<=0.05? Highlight the statistically significant factor rows (use individual p) and click run model. Interpret the output.
3. To evaluate the current design matrix with just the few main factors you determined to be significant, use DOE>Design Diagnostics>Evaluate Design. Select only the statistically significant factors for the evaluation. Look at the Alias Matrix to see what the problems are with using the same 20 runs to estimate the interaction effects (confounding of main effects and interaction effects). Specifically, we are interested in the 2-factor interaction between the biggest effects. What main factors are confounded with this interaction and what is the magnitude? Interpret the finding. (Note: find the column of the 2-factor interaction which had the largest effect. Then see what row has a number different from zero and what the main effect in that row is. The larger the absolute value the larger is the confounding. )4. Now we want to evaluate the data based on our discovery that the 2-factor interaction is confounded with another important factor. Go back to the open window you had before (DOE>Classical>Two Level Screening> Fit Two Level Screening ) and select the statistically significant factors plus the 2-factor interaction of the two biggest effects. Click Run Model again. Interpret the output. What is likely happening?5. Make a final selection on the window (DOE>Classical>Two Level Screening> Fit Two Level Screening) of what you think is the true likely factors and or interactions. Then click Run Model again. Interpret final model. Prepare the report using the following formatting guidelines:1 page, single-spaced report using 0.5 margins and two-column format1 page for appendixInclude title of report, then FirstName, LastName, ISDS course #, Assignment #, date (00/00/00)10 pt Font Calibri or Times New RomanJustified as sample reportCreate headings for each sectionList any references used (e.g. Module 1 Resources)Include a title for your report e.g. "Text Analysis of Workers Compensation Claims" and create headings for each sectionInclude supporting relevant figures from the analysis in your AppendixSubmit as pdf with filename first name initial last name and assignment number (for instance HSchneider#1)Be sure to review the Assignment Rubric and Assignment Example attached below. If you have any questions, please post in the Module Questions Forum.
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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