omula Practice Scho x9 Desmos Calculator | Schoology Xsignments/4589425093/mydocumentckboard LearnO LANGUAGEI Live ed Intro to CS Fall 20* Member Login -USO Algebra CalculatorDeltaMathSubmit Assignmentla Practice - 7196344Tools Add-ons HelpLast edit was Seconds agoal text -13 + BIUAE. IE E E - E EMontserrat3422, 11, 0, -1An=al+(n-1)d;Al=22d=-116, 12, 18, 2477, 74, 71, 68-8, -10, -12, -1410, 17, 24, 3199, 83, 67, 5l9, -19, -29, 392, 4, 6, 8Support I Schoology Blog PRIVACY POLICYI Terme of UseKDELL6.8.4yued.fgjknCValtct

In AP First term is a1 , common difference is n and number of term is n Last term nth term of an AP…

Answered: 22, 11, 0, -11 An-al+(n-1)d; Al=22…

22, 11, 0, -11 An-al+(n-1)d; Al=22 d=-11 6, 12, 18, 24 77, 74, 71, 68 8, -10, -12, -14 10, 17, 24, 31 99, 83, 67, 51 9, -19,-29, 39 2,4, 6, 8

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 35EQ

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Consider the following panel model to examine the effect of retirement on consumption expenditure, consit, of individual i over years t=1,…,3: (B1) log⁡(consit) = β0 + β1retiredit + β2ageit + β3marriedit + β4healthit + δ1Yr2t + δ2Yr3t + ai + uit Where: retiredit is a dummy variable equal to 1 if individual i is retired on year t and 0 otherwise ageit is the individual's age in years marriedit is an indicator variable for whether the individual is married (1) or not (0) in year t healthit is an indicator variable equal to 1 if the individual is in 'good health' and 0 otherwise Yr2 is a dummy variable equal to 1 in year t=2 and 0 otherwise Yr3 is a dummy variable equal to 1 in year t=3 and 0 otherwise Using the information above, answer the following 3 questions. [i] Give two (2) examples of the kind of variables captured by the term ai in Model (B1). [ii] What is the crucial assumption we must make so that the random effects (RE) estimator is consistent? Under this assumption, why is…
Use log21=0,log22=1, and log24=2 to estimate log23.
We estimate the following model for wages for major league baseball players: ln⁡(salary)= β0 +β1years + β2gamesyr + β3frstbase + β4scndbase + β5shrtstop + β6thrdbase + β7outfield + u where ln(salary) = the natural log of a player’s salary years = the player’s years in the major league gamesyr = the player’s average number of games played per year and frstbase, scndbase, shrtstop, thrdbase and outfield are each a dummy variable equal to 1 if the player plays that position on the field (when their team is fielding) and 0 otherwise. These are mutually exclusive dummy variables and there is one omitted fielding position, catcher. We find: *Regress lsalary years gamesyr frstbase scndbase shrtstop thrdbase outfield Source SS df MS Model Residual 300.454626 191.720909 7 345 42.9220894 0.55571278 Total 492.175535 352 1.39822595 lsalary coef. std. err. t P > |t| [95% Conf. Interval] years 0.0672574 0.0125509 5.36 0.000…
MARKET CAPITALIZATION is taken as a variable to be predicted, the rest are the predictors Create the following variables in the excel sheet: 1. Change Total Assets to ‘Log(Total Assets)-LogTA, 2. create a new variable called CR (CR= current assets/current liabilities), 3. Create a new variable called DR (DR= Total Debt/Total Asset), 4. Change Market Capitalization to Log(Market Capitalization)-LogMCAP Focus on LogMCAP, LogTA, CR, DR, EBIT, LogMCAP to be predicted, the rest are predictors for the purpose of completing the assignment. 1. Perform a descriptive analysis in R , using the variables given . 2. Design a structure to show the training data, testing data, and discuss the validation process using your dataset. 3. Perform a regression analysis, show the clearly and discuss on the predictive power using the forecast figures and coefficients. 4. You may include scatter plots to address the significance of the predictors, OR extend your analysis by using other statistical…
Consider a simple model to explain a country’s alcohol related automobiles incidents (totaai) in terms of police police officers (topps): Estimating (a) using quarterly data from 1991-2024 gives: log(totaait) = 12.58 − 0.66 log(topps); (2.22) (0.33) n = 95; R2 = :439; 2. Test the null hypothesis that the coefficient on the log(topps) has no effect on the log(totaait) at the 5% level. 3. Suppose that both total alcohol incidents (totaai) and total police officers (totts) have a positive trend. Given this information, discuss whether the OLS estimates of ˛1 from equation (a) is unbiased (i.e., E(˛ˆ 1) = ˛1)?
It has been noted that the amount of time people spend shopping in supermarkets has decreased due to the global pandemic. Based on this realization, the manager of Power Supermarket decided to collect data for the length of time people spend in his supermarket during a one week period. He is aiming to use the data to help him decide if the supermarket should be converted to a virtual supermarket/a delivery based one. Before the pandemic Time Frequency 1-5 50 6-10 25 11-15 22 16-20 80 20-25 60 25-30 45 30-35 35 After the pandemic Time Frequency 1-5 30 6-10 65 11-15 45 16-20 50 20-25 35 25-30 40 20-35 35 Use the information above to construct two frequency polygons. Do you think that Power Supermarket should close their doors? Explain your answer. *Assume that a person who spends more time in a supermarket buys a lot of goods and a person who spends a short time in a supermarket,…
What if the model is a conditional logistic model? Will the answer be anything different? Thank you.
A psychologist conducted a study to examine the nature of the relation, if any, between an employee’s emotional stability and the employee’s ability to perform in a task group. Emotional stability was measured by a written test for which the higher the score, the greater the emotional stability. Ability to perform in a task group was evaluated by the supervisor. An employee was given a 1 if they were able to perform a task in the group, and 0 if they were unable. Following output gives the results from a logistic regression analysis on the data provided by a sample of 27 employees. (a) what is the estimated logistic regression line? (b) Convert your slope estimate into an estimate for the odds ratio, and interpret the results. (c) Estimate the odds of the being able to perform in a task group for an employee with an emotional stability score of 510.
I need help with this discrete mathematics problem involving a logarithmic function
Who is the inventor of the logistic function? 1.Ludwig Ogistic 2.The iranian physicist Piver Verfraco 3.The Belgian mathematician Pierre François Verhulst.
The prices of stocks or other financial instruments are often modeled with a lognormal distribution. An investor is considering purchasing stock in one of two companies, A or B. The price of a share of stock today is $1 for both companies. For company A, the value of the stock one year from now is modeled as lognormal with parameters μ = 0.05 and σ = 0.1. For company B, the value of the stock one year from now is modeled as lognormal with parameters μ = 0.02 and σ = 0.2. a) Find the mean of the price of one share of company A one year from now. b) Find the probability that the price of one share of company A one year from now will be greater than $1.20. c) Find the mean of the price of one share of company B one year from now. d) Find the probability that the price of one share of company B one year from now will be greater than $1.20.