We are analyzing the effects of regime type on corruption withthe following model:Corruption = 10 - 0.1GDPpc - 2.0Democracywhere Corruption is an index of corruption, GDP (per capita) ismeasured in thousands of dollars, and Democracy is a dummyvariable that is equal to one if a country is a democracy and 0otherwise. What is the predicted corruption index of ademocratic country with a per capita GDP of $44,000?Enter your answer with one decimal place.

We have given the following model

Answered: We are analyzing the effects of regime…

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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Statistics and Variables: Determine whether the following variables are qualitative or quantitative.
Suppose that you are a researcher and wish to construct a linear mathematical (statistical) model that relates the number of years and the corresponding exports (million U.S.$) of a country. The constructed model may use to forecasts the future values. You have obtained the relevant data for the during of 1990 to 1995 and you have listed the data in Table 5. Table 5. Shows the list of the amount that have earned on exports Year No. 1 2 3 4 5 6 Exports 4954 6131 6904 6813 6803 8137 (a) Construct a suitable graph that explains the relationship between the number of years and the corresponding exports. (b) Construct a mathematical (Statistical) model by using least square method between number of years and the corresponding sales. (c) Interpret the slope of the estimated linear model (d) Forecast the value of exports by using the estimated linear model for the year of 2000
The condition of an independent variable being correlated to one or more other independent variables is referred to as nonlinearity. statistical significance. multicollinearity. linearity.
plz solve question (c) with explanation within 30-40 mins and get upvotes
Grade Prediction. The Statistics Department at a large university would like to predict the final grades of students in its introductory statistics course. a. If the final grade is measured as a percentage from 0% to 100%, suggest five predictor variables that might be useful in predicting final grade. b. Write the multiple linear regression model for the conditional mean of the response variable, final grade.
I’m working on practice questions, but am confused on what all would be correct and why
3. Setup: The data set "Healthy Breakfast" contains, among other variables, the Consumer Reports ratings of 77 cereals and the number of grams of sugar contained in each serving. (Data source: Free publication available in many grocery stores. Data set available through the Statlib Data and Story.) Considering "Sugars" as the explanatory variable and "Rating" as the response variable generated the following regression line: Rating = 59.3-2.40 - Sugars. and the ANOVA table Source Regression Error Total SS df MS 8654.7 1 8654.7 102.35 6342.1 75 84.6 14996.8 76 F Questions: (a) Write down the simple linear regression model and its model assumption. (b) State the null and alternative hypotheses for the model. Based on the ANOVA table, draw conclusion based on the p-value for the test. (c) Obtain Srz and the standard error se (3₁) to construct the 95% confidence interval for $₁.
C10. In Exercise 6, we examined the relationship between vears of education and hours ot television watched per day. We saw that as education increases, hours of television viewing decreases. The number of children a family has could also affect how much television is viewed per day. Having children may lead to more shared and supervised viewing and thus increases the number of viewing hours. The following SPSS output displays the relationship between television viewing (measured in hours per day) and both education (measured in years) and number of children. We hypothesize that whereas more education may lead to less viewing, the number of children has the opposite effect: Having more children will result in more hours of viewing per day. Sig. ,000 .000 a. What is the b coefficient for education? For number of children? Interpret each coefficient. Is the relationship between each independent variable and hours of viewing as hypothesized? b. Using the multiple regression equation with…
Scenario: Album Sales: A study was done to see whether getting radio airtime and spending money on advertisements accurately predicts the number of album copies sold. A random sample of 200 artists’ albums were tracked on the number of times their songs play on the central radio station, how much money (in thousands) they spent on advertisements, as well as the number (in thousands) of album copies were sold. A record company wanted to determine if there was a positive relationship between album sales and the other two variables (money spent on advertisements and number of albums sold) What is the Null and alternative hypotheses (based on context of study) in symbols and words:
An entrepreneur who owns and operates two businesses (A and B) would like to analyze their profitability. They would like your help in the analysis. They give you the annual net profit (in thousands of $) for each business from 2008-2020. Table 1: Annual Net Profits for Businesses A and B Business Year Profit Business Year Profit 2008 -50 2008 -10 2009 57 2009 30 2010 71 2010 27 2011 64 2011 22 2012 60 2012 21 2013 50 2013 20 A 2014 41 2014 24 2015 59 2015 24 2016 71 2016 32 2017 71 2017 36 2018 74 2018 37 019 81 20 40 2020 97 2020 49 a. Suppose you want to graph the distribution of profits. Explain why using only one stem- plot might not be optimal for the analysis. b. Describe the correct stemplot to use. Generate this stemplot. Explain your steps. What can you say about the distribution from this stemplot? c. When are stemplots useful? And why is that? d. Suppose that instead of having 26 observations you have 200 observations. What graph should you generate? e. What other type of…

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