A famous bike manufacturing company wants to update the on-road prices fortwo new lunched bikes with latest specifications. Ex-showroom quotes areavailable for a duration of four months for the same. The company fetched thecorresponding market data given below;Month 1Month 2Month 3Month 4Ex-showroomquotationrates for4813first bikeEx-showroomquotation11414rates forsecond bikePerform a prineipal component analysis (PCA) on the given data in order tosignificantly contribute to the risk management of the company's portfolio.

Answered: Image /qna-images/answer/83a66a81-5d03-444f-a4c3-49468c924ef8.jpg

Answered: A famous bike manufacturing company…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A'6
Convert the following values into grouped data for 20 diabetes patients: 38,36,34,32,40,36,34,37,40,38,36, 35, 37,41,36,38,36,41,36,30 II >
Suppose researchers at an abdominal transplant clinic are concerned about the rate of graft loss due to diabetes status prior to receiving a donor kidney. Research has shown that gender discordance, or receiving a gender from a donor of an opposite gender may increase the risk of both exposure and outcome after transplant. Assume the following tables represent the stratified analysis of the potential confounding variable. (9 points) Gender Discordance Graft Failure No Graft Failure Total Diabetes II 23 10 33 No Diabetes II 4 44 48 Total 27 54 81 Gender Concordance Graft Failure No Graft Failure Total Diabetes II 9 34 43 No Diabetes II 12 87 99 Total 21 121 142 A) Calculate the stratum specific estimates for the odds ratios in each strata. B) Observe the difference in the odds ratios. Based on observation alone, what are we likely to conclude regarding the relationship between outcome and exposure…
You are a consultant to EAI and you have received the data on theannual salaries of 2500 managers. Some of these managers have alsoindicated that they have received some training. Conduct theappropriate descriptive analyses and present a report that willenable EAI to understand its operations. The link to the data is: https://drive.google.com/file/d/1KluyxHQdEsVNA38_EWPcEgKUJomm9b67/view
please dont use excel. i need all steps.
Name the forecasting methods
The dataset HollywoodMovies - 2e contains information on 970 movies that came out of Hollywood between 2007 and 2013. One of the variables is the budget (in millions of dollars) to make the movie. What would be the relevant parameter and statistic for this problem (think -- is this categorical or quantitative)? O u: The mean budget of all Hollywood Movies made between 2007 and 2013. O p: The average proportion of budgets of Hollywood Movies made between 2007 and 2013. T: The mean budget of all Hollywood Movies made between 2007 and 2013. Op: The proportion of Hollywood Movies made between 2007 and 2013.
Answer only the requirement 2 and 3.
Base on the same given data uploaded in module 4, will you conclude that the number of bathroom of houses is a significant factor for house price? I your answer is affirmative, you need to explain how the number of bathroom influences the house price, using a post hoc procedure. (Please treat number of bathrooms as a categorical variable in this analysis) Base on the same given data, conduct an analysis for the variable sale price to see if sale price is influenced by living area. Summarize your finding including all regular steps for your method. Also, will you conclude that larger house corresponding to higher price (justify)?
does the interquartile range of a data set affect the way the data is graphed?
The questions below are based on a dataset containing the characteristics of 5,407households. In particular, we will use the following variables:- size: home size, measured in square feet.- hhinc: annual household net income, measured in euros.- owner: dummy variable equal to 1 if the living space is owned, and 0 if the livingspace is rented.- hhsize1: dummy variable equal to 1 if the number of household’s members is 1 or2, and 0 otherwise.- hhsize2: dummy variable equal to 1 if the number of household’s members is 3 or4, and 0 otherwise.- hhsize3: dummy variable equal to 1 if the number of household’s members is 5 orabove 5, and 0 otherwise.- edu: education level of household’s members. We conduct a simple regression of size on hhinc, now using robust standard errors.The regression output is reported in Table 2. Why are the estimated coefficients inTable 2 equal to the estimated coefficients in Table 1? Do the conclusions on thestatistical significance at 5% of the coefficient of…
4: Generat cuera 2. 3

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