What is the mathematical representation for the multiple logistic regression model in photo? A researcher conducted a study about the hemoglobin levels among menopausal and non-menopausalwomen. For this purpose, a data of 20 women with the following information were collected:Hemoglobin Level (g/dl), Age, and Menopausal Status (yes/no). The researcher decided to conduct amultiple logistic regression analysis to find the effects of hemoglobin level, and age on menopausalstatus. The result of the analysis is given in the table below.VariableCoefficient Standard p-Estimate Error valueIntercept -15.94 8.35Hemoglobin -2.61levelAge1.030.89 0.0030.37 0.011

Let X1 represents hemoglobin level and X2 repentance age. Y is dependent variable which represents…

Answered: A researcher conducted a study about…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
In a study investigating maternal risk factors for congenital syphilis, syphilis is treated as a binary outcome variable, where 1 represents the presence of disease in a newborn and 0 represents absence of disease. The estimated coefficients from a logistic regression model containing the predictors cocaine or crack use, marital status, number of prenatal visits to a doctor, alcohol use and level of education are included in the table below. The estimated intercept is not included in the table. Variable Coefficient Cocaine/Crack Use 1.354 Marital Status 0.779 Number of Prenatal Visits -0.098 Alcohol Use 0.723 Level of Education 0.298 The estimated coefficient of cocaine or crack use has a standard error of 0.162. Construct a 95% confidence interval for the population odds ratio comparing women who used cocaine or crack versus those who did not. Conduct a test of the null hypothesis that the coefficient associated with cocaine or crack use is…
The following table contains statistics from a logistic regression analysis for a study on intravenous drug use among high school students in United States. Drug use is characterized as a dichotomous variable, where 1 indicates that an individual has injected drugs within the past year and 0 that he or she has not. Factors that might be related to drug use are instruction about the HIV in school (1 represents "had HIV education" and 0 represents "did not have HIV education"), age of the student (in years), and gender (1 represents male and 0 represents female). Statistics in the table are estimated coefficients of the logistic regression model and p-values for testing the significance of the coefficients. Choose proper answers using statistics in the following table. (THERE MAY BE MORE THAN ONE CORRECT ANSWER) Variable Coefficient p-value Intercept (Constant) -0.164 0.078 HIV instruction 0.019 0.928 Age 0.064 0.036 Gender 1.032 0.014…
The National Survey of Drug Use and Health is a large annual cross-sectional survey of drug use in the United States. Using data from this survey, researchers wanted to assess the relationship between region in the country (Northeast, Midwest, South, and West) and past-month marijuana use among 18-25-year-olds. They obtained the following logistic regression model from the data: 1)What are the log odds of past-month marijuana use among 18-25-year-olds in the Midwest? 2)What is the probability of past-month marijuana use among 18-25-year-olds in the Northeast? 3)The odds of past-month marijuana use for 18-25-year-olds in the South is _______ times the odds of past-month marijuana use for 18-25-year-olds in the Northeast.
The dating web site Oollama.com requires its users to create profiles based on a survey in which they rate their interest (on a scale from 0 to 3) in five categories: physical fitness, music, spirituality, education, and alcohol consumption. A new Oollama customer, Erin O'Shaughnessy, has reviewed the profiles of 40 prospective dates and classified whether she is interested in learning more about them. Based on Erin's classification of these 40 profiles, Oollama has applied a logistic regression to predict Erin's interest in other profiles that she has not yet viewed. The resulting logistic regression model is as follows: For the 40 profiles (observations) on which Erin classified her interest, this logistic regression model generates that following probability of Interested. Probability of Probability of Observation Interested Interested Observation Interested Interested 35 1 1.000 13 1 0.412 21 1 0.999 2 0 0.285 29 1 0.999 3 0 0.219 25 1 0.999 7…
The dating web site Oollama.com requires its users to create profiles based on a survey in which they rate their interest (on a scale from 0 to 3) in five categories: physical fitness, music, spirituality, education, and alcohol consumption. A new Oollama customer, Erin O'Shaughnessy, has reviewed the profiles of 40 prospective dates and classified whether she is interested in learning more about them. Based on Erin's classification of these 40 profiles, Oollama has applied a logistic regression to predict Erin's interest in other profiles that she has not yet viewed. The resulting logistic regression model is as follows: For the 40 profiles (observations) on which Erin classified her interest, this logistic regression model generates that following probability of Interested. Probability of Probability of Observation Interested Interested Observation Interested Interested 35 1 1.000 13 0 0.412 21 1 0.999 2 0 0.285 29 1 0.999 3 0 0.219 25 1 0.999 7…
A logistic regression was used to investigate obesity and poor physical health while controlling for the following variables: age, gender, race, income, health status, education, current smoker, and diet/exercise status. Justify the use of a logistic regression.
Explain which characteristic of the STA leads to a consideration of a logistic model as opposed to a linear regression mode.
An experiment is conducted to see the effect of light intensity on plant growth, what is the dependent variable in this scenario?
Life insurance companies are keenly interested in predicting how long their customers are likely to live, because this will determine their premiums and ultimately their profitability. An Australian life insurance company is interested in the relationship, if any, between the age at death of their male customers and that of the customer’s father. Data are collected on a random sample of 100 of their male customers who have recently died. The customer’s age at death was plotted against that of their father and a linear regression model applied. Relevant output is shown below. Say how you know from the output that there actually is a significant linear relationship between a male customer’s age at death and his father’s age at death. State the value of the coefficient of Father’s Age (Death) and interpret this value in the context of the problem at hand.State the value of the coefficient of determination in the model and interpret this value in the context of the situation.
Life insurance companies are keenly interested in predicting how long their customers are likely to live, because this will determine their premiums and ultimately their profitability. An Australian life insurance company is interested in the relationship, if any, between the age at death of their male customers and that of the customer’s father. Data are collected on a random sample of 100 of their male customers who have recently died. The customer’s age at death was plotted against that of their father and a linear regression model applied. Relevant output is shown below Examine both the scatterplot and the correlation matrix provided above. Comment on the apparent relationship between the customer’s age at death and their father’s age at death in the plot. Explain how the information in the correlation matrix supports your conclusion
What choice is the best representation of the related logistic regression model?

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