11. A small-business Web site contains 100 pages and 60%, 30%, and 10% of thepages contain low, moderate, and high graphic content, respectively. A sample offour pages is selected without replacement, and X and Y denote the number ofpages with moderate and high graphics output in the sample. Determine(a) fxy(x, y)(b) fx (x)(c) E[X](d) fy|3 (y)(e) E[Y|X = 3}(f) V[Y|X = 3](g) Are X and Y independent?

A small business contains 100 pages60% of pages contain low graphic context30% of pages contain…

Answered: 11. A small-business Web site contains…

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 gardener applied chemical "Z" to plants in a flower bed. (S)he observed that the plants grew dramatically during the next two weeks. Using only the information from the previous two sentences, write a hypothesis about the effect of chemical "Z" on plants. (Note: Your hypothesis must be a testable statement.) A researcher conducted a series of experiments to test the effect of chemical “Z” on plants. The data from the experiments is summarized in the graph below. (Image of the Graph attached.) Interpret the graph above. What did the researcher learn about the effect of chemical “Z?” Based on the researcher’s graph, what can you conclude about the hypothesis you wrote for Question 7 above?
The marketing research department of a large company knows that the company's monthly sales are influenced by the way in which it spends money on marketing. For example, monthly expenditures such as the ones listed below are known to have an effect on y, the company's total monthly sales (in millions of dollars). X1 = money spent on television advertising (in 1000's of dollars) X2 money spent on promotion (i.e., free samples) X3 = money spent on newspaper advertising (in 1000's of dollars) X4 average discounts offered to retail outlets (in %) Using data from the previous 18 months, the company decides to collect data on 6 of the independent variables to use in a multiple regression model for estimating monthly sales. If the R´ for this model is 0.93, fill in the missing entries in the ANOVA table associated with this model. Do all calculations to at least three decimal places.
8. Find the line of best fit y = a + bx for the data points (1,3), (2,4) and (-1,-1).
A)Test the claim, at the a = 0.10 level of significance, that a linear relation exists between the two variables, for the data below, given that y-1.885x +0.758. -5 |-3| 4 11 6 y Step 1) State the null and alternative hypotheses. Step 2) Determine the critical value for the level of significance, a. Step 3) Find the test statistic or P-value. Step 4) Will the researcher reject the null hypothesis or do not the null hypothesis? Step 5) Write the conclusion. B) The regression line for the given data is v = -1.885x + 0.758. Determine the residual of a data point for which x = 2 and y = -4. SAMSUNG DII 96 &
J. 1. Find out co-efficient or correlation from the following: x= 40 50 55 45 50 -60 65 65 70 80. y= 10 12 13 11 12 15 18 18 21 30.
Illustration. 21.22. Comment criticaly on the following state- ments: (a) Road accidents resulted in 4513 deaths in 1958 and 5250 in 1967 while the number of women drivers increased in the period. Hence women make bad drivers. (b) Of 300 persons inoculated against influenza during the epide- mic only 12% were affected. This shows a marked improvement com- paring with the remainder of the population for which the equivalent igure was 28%.
15) The intercept is 0, the autoregressive coefficient is 0.2 and the moving average coefficient is 0.5 in an ARIMA(1,1,1) model. What is the one-step ahead forecast if the shock for the current period is -2 and the current and one-period lagged values of the forecast variable are 110 and 105?
I have collected real data on the sale of a microwavable cup of soup across 20 different cities for the same time period (a month). The variables in the dataset are: Quantity sold in the city for that month: Measured in thousands of units Price: measured in dollars Average Income in the city: Measured in thousands of dollars Ads: Average number of ads run in stores for that city during that month. Price of a substitute product: measured in dollars Population of the city: measured in thousands of people The dataset is on Canvas and, using Excel or any other statistical software, please answer the following questions: 1. Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics. Graphs are welcome as well. 2. Take the logs of the variables, and estimate the demand function. a. Interpret the R-square. b. Interpret the coefficients for logP and logPsub c. Interpret the p-values associated with each independent…
4. Suppose you are given the following information: = 49.6870 – 2.1586X; r2 = 0.9757 (0.7463) (0.12113) df=8 T= (66.578) (-17.821) p-value = (0.000) (0.000) a) Conduct a two tailed hypothesis test that: i) The intercept is 49 and the slope coefficient is -2, use 1% significance. ii) Confirm your deductions to 4(a) (i) using a confidence interval approach b) What does the r2 tell you? c) Perform a hypothesis using r2, such that p=D0, what do you conclude?
Approximate f(4) for the following set of data using cubic spline: [0, 1], [3, 2], [8, 3]
Freshcrim specializes in the sales of ice cream from street trolleys in the centers of many cities. Some factorsthat may determine the sales of ice cream are: the atmospheric temperature, the location of the trolley, therain and the humidity. However, there exists a hypothesis that the sales of ice cream during the summer aresignificantly correlated only with atmospheric temperature. They defined two variables: X : the meanatmospheric temperature and Y : the sales. They considered the month of July of this year in a randomsample of 30 cities. For each city in the sample, let x be the mean temperature in degrees Fahrenheit and ythe mean sales per day in dollars per 100,000 residents. The data are given below. A regression model wasrun, with Y as the dependent variable and X as the independent variable.
Consider a two-dimensional scatterplot representing the relationship between two continuous variables. If the correlation coefficient is -1, then: a. All points lie in a straight line with a slope of -1. b. All points lie in a straight line with an unknown negative slope. c. All points do not lie in a straight line but the best fitting regression line has a slope of -1 d. There is a strong positive relationship between the two variables.

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