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- A company is keen on investing in expanding its market penetration in Africa opening an on-line shop to new potential African clients. For this reason, the company wants to understand the level of digital divide, measured by the total number of internet users in relation to total population, as a function of clients’ personal characteristics. Considering the following analysis based on a survey conducted in two main markets, Nigeria and Kenya, we have the following information to estimate the digital divide: Age: respondent’s age from 25 to 55 years old. Gender: 1 female, 0 male. Education level measured as years of schooling. Region: Kenya =1, Nigeria =0. As part of their work they have produced the following linear regression. How well does the model “describe/explain” the digital divide? How would you improve the model? Is the model statistically significant?A company is keen on investing in expanding its market penetration in Africa opening an on-line shop to new potential African clients. For this reason, the company wants to understand the level of digital divide, measured by the total number of internet users in relation to total population, as a function of clients’ personal characteristics. Considering the following analysis based on a survey conducted in two main markets, Nigeria and Kenya, we have the following information to estimate the digital divide: Age: respondent’s age from 25 to 55 years old. Gender: 1 female, 0 male. Education level measured as years of schooling. Region: Kenya =1, Nigeria =0. As part of their work they have produced the following linear regression. Comment on the statistical significance, relative strength and direction of the relationships between the dependent variable and the independent variablesA company is keen on investing in expanding its market penetration in Africa opening an on-line shop to new potential African clients. For this reason, the company wants to understand the level of digital divide, measured by the total number of internet users in relation to total population, as a function of clients’ personal characteristics. Considering the following analysis based on a survey conducted in two main markets, Nigeria and Kenya, we have the following information to estimate the digital divide: Age: respondent’s age from 25 to 55 years old. Gender: 1 female, 0 male. Education level measured as years of schooling. Region: Kenya =1, Nigeria =0. As part of their work they have produced the following linear regression. How well does the model “describe/explain” the digital divide? How would you improve the model? Is the model statistically significant? Can we conclude that education definitely impacts on the digital divide? Justify your answer from a theoretical point…
- Which of values of x on this graph is the relative minimum?Show algebraically whether the given functions are injected or not.Life Expectancy at 65 Using data for selectedyears from 1950 and projected to 2050, the functiony = 0.077x + 13.827 gives the life expectancy atage 65, with y equal to the number of additional yearsof expected life at age 65 and x equal to the numberof years after 1950.a. Why is this a linear function?b. Find and interpret the slope of the graph of thisfunction.(Source: Social Security Administration)