We have measurements from eight companies for the % workforce change in 2010from 2009 and the % change in profits from 2010 to 2011.% workforce change (x): 1.0% profit change (y):1.5 -0.4-2.6 -3.8 -5.8 -2.5 -0.10.4 0.4 0.1-0.2 -0.5 -7.5 0.20.3We can calculate: Er = -12.7, Ex² = 64.51,Συ--6.8 , Σ 57, Σεy- 46.35.Find the sample correlation between the two variables, and fit a simple linear modelto the dataset.Also, plot the residuals, ri, against xi, and comment on the fit of the model.

Data given : X(%work force change) Y(%profit change) We have to find out correlation between the two…

Answered: We have measurements from eight…

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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Please help question 101
Many factors influence the retail price of gasoline. Suppose the following table shows the average retail price for a gallon of regular grade gasoline for each year from 2011 through 2014. (Round your answers to one decimal place.) Year Average Price ($) 2011 3.526 2012 3.608 2013 3.505 2014 3.368 (a) Use 2011 as the base year and develop a price index for the retail price of a gallon of regular grade gasoline over this four-year period. 2011 price index 2012 price index 2013 price index 2014 price index (b) Use 2012 as the base year and develop a price index for the retail price of a gallon of regular grade gasoline over this four-year period. 2011 price index 2012 price index 2013 price index 2014 price index
How do you calculate the benchmark daily returns of weightings 60% IWV, 20% EFA, and 20% AGG.
Below are percentages for annual sales growth and net sales attributed to loyalty card usage at 74 Noodles & Company restaurants. Annual Sales Growth (%) and Loyalty Card Usage (% of Net Sales)(n = 74 restaurants) Store Growth% Loyalty% Store Growth% Loyalty% 1 -8.3 2.1 38 7.1 1.6 2 -4.0 2.5 39 7.4 1.8 3 -3.9 1.7 40 7.7 2.2 4 -3.4 2.1 41 7.9 2.2 5 -3.3 2.5 42 8.1 2.8 6 -1.9 3.0 43 8.3 2.4 7 -0.8 2.3 44 8.5 3.1 8 -0.4 2.3 45 8.6 2.2 9 -0.2 2.2 46 8.7 1.3 10 -0.2 2.3 47 8.8 1.8 11 0.5 2.1 48 8.8 2.5 12 0.6 2.5 49 8.9 1.9 13 0.8 2.0 50 9.1 2.0 14 1.9 2.0 51 9.5 2.4 15 2.0 2.0 52 10.2 2.2 16…
5. The following map shows the job growth rates for each state in the US. Use the map to determine how many states had between 2.5% and 6.9% job growth. Job Growth By State 7% or more (15 states) 4.5% to 6.9% (10 states) 2.5% to 4.4% (2 states) less than 2.5% (11 states) Losing Jobs (12 states)
The rate of return for the last 19 years of a certain segment of the stock market is given in the table. (The data is also provided below the table as a comma-separated list to make it easier to copy.) Market Segment Rate of Return, 2002-2020 Year Rate of Return (%) 2020 3.23 2019 6.14 2018 11.39 2017 15.99 2016 3.24 2015 -3.86 2014 -1.04 2013 8.49 2012 5.93 2011 6.96 2010 1.98 2009 3.13 2008 -6.55 2007 7.27 2006 3.02 2005 -1.34 2004 7.28 2003 6.27 2002 -0.76 Rate of Return (%): 3.23, 6.14, 11.39, 15.99, 3.24, -3.86, -1.04, 8.49, 5.93, 6.96, 1.98, 3.13, -6.55, 7.27, 3.02, -1.34, 7.28, 6.27, -0.76 Find the 34th percentile of the data. 6.46
Repair revenues from labor costs of the bicycle shop are given below: X 7.1 2.2 7.2 3.1 3.3 3.5 7.7 4.1 6.8 4.7 5.3 5.5 6.1 Y 3.9 1.7 3.7 1.5 2.2 1.4 4.9 2.5 4.5 3.4 2.3 3.6 3.2 Determine whether there is significant relationship at 0.05 level of significance Predict the value of Y if x are 2.7 and 1.5.
12 In 1976 the average price of a commodity was 20% more than in 1975 but 20% less than in 1974 and it was 50%more than in 1977. Reduce the data to price relatives. (i) Using 1975 as base (ii) With 1974-1975 as base average
Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPI) and the cost of a slice of tuna. We would like to build a model using the CPI to predict the cost of a slice of pizza in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 Cost of a slice of tuna(y) 0.15 0.35 1.00 1.25 1.75 2.00 Plot the data. Are we justified in creating a Linear Regression model to predict the price of a pizza slice using the CPI? Why or why not? Calculate the descriptive statistics. Calculate the sums of squares Calculate the slope, intercept, and correlation. What is this correlation value telling us? Assemble the prediction equation, and interpret the slope within the context of the problem. State the hypotheses for the hypothesis test for regression.
You collect data of average annual returns for Amazon Stock and Microsoft Stock and make the following table: (This data can be copied into Excel.) Year Amazon Return Microsoft Return 2013 0.5896 0.1221 2014 -0.2218 0.2416 2015 1.1778 0.1944 2016 0.1095 0.1200 2017 0.5596 0.3766 2018 0.2843 0.1874 2019 0.3216 0.5526 You use this data to answer the research question: are true population Amazon Returns greater than true population Microsoft Returns?
Can you guys help me on this? Thank you!
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Price/Book Value Ratio Return on Equity 13.032 1.405 8.305 2.113 6.654 1.239 3.262 2.449 5.291 2.398 7.719 0.353 2.569 7.593 5.104 2.012 4.797 2.182 4.129 1.918 1.549 1.951 5.046 2.417 2.159 3.011 1.725 5.582 4.698 Growth% 6.385 11.846 135.669 12.459 0.073 25.092 14.188 8.804 22.766 38.082 18.985 25.696 24.519 19.666 11.624 22.849 49.965 69.649 36.696 3.819 41.139 9.218 29.108 17.772 25.114 29.295 23.764 31.405 9.497 14.759 18.541 12.026 39.016 14.228 39.439 14.097 27.022 14.841 13.237 20.669 17.311 14.887 15.849 5.601 16.775 11.172 8.401 16.161 18.404 23.973 16.673 14.725 46.605 28.839 52.021

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