Opening the paper…
Business Analytics, Quiz 2
Data on “Urban Population (UP)” of a country and the “GDP” of the same country are collected. The “GDP” is captured as a percentage (that is “10.5%” is captured as “10.5”) and the “UP” is captured in crores of people (that is “1,20,00,000” is captured as “1.2”). From the raw data, the analyst has identified that the relation is non-linear. Hence, the analyst applies a natural logarithmic transformation on both variables (the independent variable is “GDP” and the dependent variable is “UP”). The transformed data is modelled as a Simple Linear Regression and the developed model is presented in Figure-1. Using this information, answer the given subquestions.
How many degrees of freedom will be present for the “Regression” term in the ANOVA table (nomenclature as per excel)?
Data on “Urban Population (UP)” of a country and the “GDP” of the same country are collected. The “GDP” is captured as a percentage (that is “10.5%” is captured as “10.5”) and the “UP” is captured in crores of people (that is “1,20,00,000” is captured as “1.2”). From the raw data, the analyst has identified that the relation is non-linear. Hence, the analyst applies a natural logarithmic transformation on both variables (the independent variable is “GDP” and the dependent variable is “UP”). The transformed data is modelled as a Simple Linear Regression and the developed model is presented in Figure-1. Using this information, answer the given subquestions. Figure from the passage in the original paper How many degrees of freedom will be present for the “Regression” term in the ANOVA table (nomenclature as per excel)? Data on “Urban Population (UP)” of a country and the “GDP” of the same country are collected. The “GDP” is captured as a percentage (that is “10.5%” is captured as “10.5”) and the “UP” is captured in crores of people (that is “1,20,00,000” is captured as “1.2”). From the raw data, the analyst has identified that the relation is non-linear. Hence, the analyst applies a natural logarithmic transformation on both variables (the independent variable is “GDP” and the dependent variable is “UP”). The transformed data is modelled as a Simple Linear Regression and the developed model is presented in Figure-1. Using this information, answer the given subquestions. Figure from the passage in the original paper If the GDP in 2024 was 15%, then what is the predicted “UP” (in crores of people) based on the SLR model? *(Note: Enter your answer rounded to two decimal places. For example, if your answer is “1.235”* *then enter it as “1.24”)* Milo’s Bakery is famous for three products “BA Biscuits (BAB)”, “TA Controversy Cake (TACC)” and “Hot Argument Drink (HAD)”. Dr.Milo, the owner of the shop, is an aspiring data analyst. He has collected 5 days of data. On each day, he captures the number of each product made and total kilogram of cooking gas consumed. Using all the collected data, Dr.Milo has built a linear regression model in excel, and the partial regression output is provided in Figure-2. Using this information, answer the given subquestions. | *Regression Statistics* | | |---|---| | Multiple R | | | R Square | | | Adjusted R Square | 0.97 | | Standard Error | 3.36 | | Observations | | ANOVA | | *df* | *SS* | *MS* | *F* | |---|---|---|---|---| | Regression | | Q2 | | Q5 | | Residual | Q1 | Q3 | | | | Total | | Q4 | | | | | *Coefficients* | *Standard Error* | *t Stat* | *P-value* | |---|---|---|---|---| | Intercept | 23.8 | 13.2 | | 0.32 | | No. of BAB made | 0.18 | 0.05 | | 0.17 | | No. of TACC made | 0.32 | 0.16 | | 0.3 | | No. of HAD made | -0.008 | 0.1 | | 0.95 | Figure-2: Partial Regression Output from Excel What is the sample size for building the model in Figure-2?