A study is conducted to determine the height of a beetle is distinctively differentamong other insects. The researcher randomly selected 25 insects. Each insectwas classified as either a beetle or other and the height (in inches) was measured.The data was recorded in "beetle_ex6.xlsx" inside the "beetle" tab.R Software output and Confusion Matrix> Logit Model SummaryCoefficients:Estimate Std. Error z value Pr(>1z1)(Intercept) -6.41906 6.18612 -1.038 0.299Height 0.08949 0.08927 1.002 0.316> Wald's TestModel 1: Insect HeightModel 2: Insect - 1#DF Loglik of Chisq Pr(>Chisa)12-16.62421-17.148 -1 1.0483 0.3059> Confusion MatrixInsect (Truevalue)0 (Other)1 (Beetle)TotalPredictedProbabilityлз0.5(0)10717> 0.5(1)8T-otal141-255125a) Construct the logistic regression model both in terms of probability and log odds.b) Interpret the coefficient of the model constructed in terms of odds.c) Calculate the sensitivity, specificity and accuracy of the model (# of correctlypredicted/number of samples *100)

For the linear regression model of y=a+bx with a provided odd ratio of occurring of an event, the…

Answered: A study is conducted to determine the…

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 researcher collected a data set for a random sample of 930 individuals living in and around London, with data collected over 1-year period. The Table below reports the OLS coefficient estimates (intercept not reported) and standard errors (in parentheses), where the dependent variable is [100xIn(well-being)]. Commuting time/60 -0.267 (0.039) -0.14 (0.040) Age Age squared/100 0.12 (0.040) Hours worked -0.0053 (0.001) log real income 0.0267 (0.009) Married or cohabiting 0.589 (0.032) Num. of children. -0.051 (0.015) Saves Degree 0.299 (0.022) -0.022 (0.035) The explanatory variables are: Commuting time = Number of minutes of commuting time per day; Age= Age in years; Hours worked = Hours worked per week; Log of real household income = 100xLn(real household income measured in £10,000s); Num. of children = Number of children under the age of 18; Save regularly = 1 if save regularly, 0 otherwise; University degree = 1 if has a University degree, 0 otherwise. Calculate the test statistics…
Define Regression Methods?
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “State Island”). Write down the population model that assumes the effect of mother’s AGE at birth on infant weight BW is DIFFERENT for different levels of maternal smoking status (MSS) when adjusted for BOROUGH variable. Specify the name of each predictor in the model and/or what it means. Make sure that it is clear what each predictor means.
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
In a regression analysis if SSE = 64 and SSR = 364, then what is the coefficient of determination? (please keep 2 decimal places)
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). Questions: 1.Write down the population model that estimates BW based on variables AGE and BOROUGH(with the dummy variables). Make sure that it is clear what each predictor means. 2.How many parallel lines are computed by model from population model you created above? 3.Write down the population model that estimates BW based on variables AGE, MSS(with their dummy variables) and BOROUGH(with their dummy variables). Also write down the number of parrallel lines.…
Please look at the following regression table. The year is 2010. The data originates from the Penn World Table 9.0, from Harris et.al. 2014 from the World Bank and from the International Energy Agency. The variables are defined as follows: Lntran_pc = log of transportation energy consumption per capita (ktoe) Lnypcpenn =log of GDP per capita (USD) Ln_gasprice = log of pump price for gasoline (USD/liter) Ln_temperature = log of the average annual temperature (in C) Ln_annualprecip= log of annual precipitation (mm) Ln_land = log of the land area of a country OECD = a dummy (indicator) that takes on the value of 1 if the country is OECD member, zero otherwise. Please define (Gauss Markov) MLR 4, state if it is likely to hold or not in this case.
Please anwser using SPSS!
The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.25*SM_DOLLARS + 1.5*RADIO_ADS + 1.2*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. Initially, $320 was spent on social media ads, 10 radio ads were aired, and $120 spent on web search ads. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $440 without changing the…
Describe three approaches to modeling seasonality in a regression forecast.
How to do a multi regression model using excel

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