From the following observations of annual EPS for a company, what is the first-orderautocorrelation?Time EPS13.8823.414.184.215.425.963456Note that using the CORREL() spreadsheet function will not produce the correct result. Thoughfor a large sample it'll be really close, for a small sample such as this one the difference can besignificant. This is because for the autocorrelation you use the variance of the full sample in thedenominator, as well as use the full sample to find the mean for use in covariance. In contrast,the CORREL function will treat the two subsets of the time series as separate data, and calculateseparate mean and standard deviation for each.

Given the data as Time EPS 1 3.88 2 3.41 3 4.18 4 4.21 5 5.42 6 5.96

Answered: From the following observations of…

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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Suppose you have access to a database with the variables listed below. Using the two variables BMI(the predictor) and diabetes(the outcome) Name two types of descriptive statistics you could report specifying the variables BMI and diabetes.
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Fiske Corporation manufactures a popular regional brand of kitchen utensils. The design and variety has been fairly constant over the last three years. The managers at Fiske are planning for some changes in the product line next year, but first they want to understand better the relation between activity and factory costs as experienced with the current products. Discussions with the plant supervisor suggest that overhead seems to vary with labor-hours, machine-hours, or both. The following data were collected from last three year's operations: Quarter Machine-Hours 18,850 4 5 6 7 8 9 10 11 12 18,590 17,480 19,240 21,280 19,630 19,240 18,850 18,460 20,670 17,550 18,460 Labor-Hours 15,605 15,484 16,727 15,990 17,508 17,376 15,297 14,373 16,001 17,002 14,285 17,651 Factory costs $ 3,395,671 3,425,836 3,617,844 3,573,940 3,812,984 3,778,012 3,532,426 3,369,802 3,513, 187 3,731,434 3,325,615 3,724,486 Required: Prepare a scatter graph based on the factory cost and labor-hour data. Note: 1.…
1. The data in Table 7–6 were collected in a clinical trial to evaluate a new compound designed to improve wound healing in trauma patients. The new compound was com- pared against a placebo. After treatment for 5 days with the new compound or placebo, the extent of wound healing was measured. Is there a difference in the extent of wound healing between the treatments? (Hint: Are treatment and the percent wound healing independent?) Run the appropriate test at a 5% level of significance. Use the data in Problem 1. Pool the data across the treatments into one sample of size n = 250. Use the pooled data to test whether the distribution of the percent wound healing is approximately normal. Specifically, use the following distribution 30%, 40%, 20%, and 10% and a = 0.05 to run the appropriate test. Percent Wound Healing Treatment 0-25% 26-50% 51-75% 76-100% New compound (n=125) 15 37 32 41 Placebo (n=125) 36 45 34 10
This dataset of size n - 51 is for the 50 states and the District of Columbia in the United States. The variables are - year 2002 birth rate per 1000 females 15 to 17 years old and z- poverty rate (the percent of the state's population living in households with in- comes below the federally defined poverty level) i- 13.1 - 22.3 R- 51, Su - E(-2) - 914.7 S, - E( -2)( - 6) - 1, 256.2 Su - E(m - M) - 3, 249 SSE - E(w - - 1, 509.6 1. Find A. A and r. 2. Write the fitted linear regression model for ý, in terms of z, A, and A- For A and , use the values you obtained in problem 1. 3. Interpret the slope of the least squares line based on the context. 4. Find SST, SE and SSR. 5. Find R* and . 6. Complete a chart for ANOVA df MS pvalue Source Regression Error Total 7. Complete a chart for Parameter Estimates. t-value pvalue Parameter Intercept Slope Estimate S.e. 8. What is the residual e, for the observation (.) - (20.1,31.5)? 9. What is the conclusion for the test Ha : -0 vs Ho : +0 with a -…
3.Which model do you think is the “best” reduced model? Discuss why you choose this model. Analysis of Variance Table (Step back model) Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 17.1136 0.0003079 *** sqft 1 35364 35364 28.8196 1.134e-05 *** sd 1 5961 5961 4.8576 0.0362339 * unts 1 8678 8678 7.0722 0.0130049 * gar 1 33364 33364 27.1899 1.713e-05 *** cp 1 7641 7641 6.2269 0.0189934 * Residuals 27 33131 1227 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Step forward model: Response: rent Df Sum Sq Mean Sq F value Pr(>F) age 1 21000 21000 16.6255 0.000406 *** sqft 1 35364 35364 27.9976 1.757e-05 *** sd 1 5961 5961 4.7191 0.039517 * unts 1 8678 8678 6.8705 0.014697 * gar 1 33364 33364 26.4144 2.599e-05 *** cp 1 7641 7641 6.0493 0.021176 *…
The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means. For the following data, the scores are the same as above except that the difference between treatments was reduced by moving the third treatment closer to the other two samples. In particular, 3 points have been subtracted from each score in the third sample. Before you begin the calculation, predict how the changes in the data should influence the outcome of the analysis. That is, how will the F-ratio for these data compare with the F- ratio from above? Treatment A F-ratio= = p-value = 6 5 4 LO 5 5 Treatment B Treatment C 5 6 8 4 6 8 7 7 4 10

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