Q3 a) A researcher wants to find out what are the factors which determine the number ofinstalls (I) of an application (app) from a famous app store. Size in Mbs (S), Reviews in*000s (Re), Ratings (0 to 5) (Ra), Price in 'Rs (P). She ran the following regressions:log I = 1.329 + 0.2356 S+0.4320 log(Ra) – 0.2678 P + 1.928 log(Re)Se = (0.63)R? = 0.734(0.242)(1.29)(0.001)(0.156)df = 156i. Interpret the regression above.ii. Test for statistical significance of Price in the model. Depending on the result do yousuggest that price is a significant factor affecting app installation?iii. Suppose the regression is re-estimated where number of installs (I) varies only withrespect to price (P). Average I in sample is 5 and average P is Rs 8.9. Followingregression was estimated:I = 52.351 + 3.139 -se = (37.39) (0.0187)df = 156, R? = 0.806How would you interpret this model? Explain the shape of the curve.iv. What would be the slope and elasticity of number of installs with reference to theequation given in iii) above?v. How would the equation in iii) change if we suggest that number of app installationsvaries with respect to the kind of cellular phone used by the customer, that is android orios phones?b) Will a dummy variable trap always exist if the number of dummies taken for a variableis same as the number of categories of that variable?c) Show that the coefficient of determination, R2, can also be obtained as the squaredcorrelation between actual Y values and the Y values estimated from the regression modelwhere Y is the dependent variable.

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a) A researcher wants to find out what are the factors which determine the number of installs (I) of an application (app) from a famous app store. Size in Mbs (S), Reviews in *000s (Re), Ratings (0 to 5) (Ra), Price in 'Rs (P). She ran the following regressions: log I = 1.329 + 0.2356 S +0.4320 log(Ra) – 0.2678 P + 1.928 log(Re) Se = (0.63) R = 0.734 (0.242) (1.29) (0.001) (0.156) df = 156 %3D

a) A researcher wants to find out what are the factors which determine the number of installs (I) of an application (app) from a famous app store. Size in Mbs (S), Reviews in *000s (Re), Ratings (0 to 5) (Ra), Price in 'Rs (P). She ran the following regressions: log I = 1.329 + 0.2356 S +0.4320 log(Ra) – 0.2678 P + 1.928 log(Re) Se = (0.63) R = 0.734 (0.242) (1.29) (0.001) (0.156) df = 156 %3D

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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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

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Q3 a) A researcher wants to find out what are the factors which determine the number of
installs (I) of an application (app) from a famous app store. Size in Mbs (S), Reviews in
*000s (Re), Ratings (0 to 5) (Ra), Price in 'Rs (P). She ran the following regressions:
log I = 1.329 + 0.2356 S+0.4320 log(Ra) – 0.2678 P + 1.928 log(Re)
Se = (0.63)
R? = 0.734
(0.242)
(1.29)
(0.001)
(0.156)
df = 156
i. Interpret the regression above.
ii. Test for statistical significance of Price in the model. Depending on the result do you
suggest that price is a significant factor affecting app installation?
iii. Suppose the regression is re-estimated where number of installs (I) varies only with
respect to price (P). Average I in sample is 5 and average P is Rs 8.9. Following
regression was estimated:
I = 52.351 + 3.139 -
se = (37.39) (0.0187)
df = 156, R? = 0.806
How would you interpret this model? Explain the shape of the curve.
iv. What would be the slope and elasticity of number of installs with reference to the
equation given in iii) above?
v. How would the equation in iii) change if we suggest that number of app installations
varies with respect to the kind of cellular phone used by the customer, that is android or
ios phones?
b) Will a dummy variable trap always exist if the number of dummies taken for a variable
is same as the number of categories of that variable?
c) Show that the coefficient of determination, R2, can also be obtained as the squared
correlation between actual Y values and the Y values estimated from the regression model
where Y is the dependent variable.

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