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Q.1. Justify the application of data analytics and predictive modeling in busine

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  • AuthoradminX
  • Length286 words
  • Reading time2 min

Q.1.
Justify the application of data analytics and predictive modeling in business decision-making. How do techniques such as regression analysis, time series analysis, and data mining provide valuable insights for strategic decision-making. Given such techniques, explain why real-life choices still fall short of the most ideal or optimal outcomes.
Q.2.
The following are the incomes (UGX Mil) and years of education for 20 heads of households in Kasese Municipality in Uganda:
OBS
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
EDUC
20
11
19
0
14
5
17
19
23
6
10
17
11
2
11
8
24
16
6
2
INCOME
30
8
22
3
20
3
18
20
30
9
30
16
15
20
10
8
35
15
4
2
Accurately capture the data in Microsoft Excel or SPSS
Generate scatter plots for income and educ and interpret
Compute the bivariate Pearson correlation coefficient between income and educ
Run the simple regression 𝐼𝑛𝑐𝑜𝑚𝑒 = 𝛽0 + 𝛽1𝑒𝑑𝑢𝑐 + 𝜖 a and save the output
Interpret the intercept (β0) and slope coefficients (β1)
Report and interpret the R2
Q.3.
The data below shows the gender and work experience of the heads of household in question 3. Note that the gender variable is coded as 1= male, and 2 = female.
GENDER
1
2
1
2
1
2
1
1
1
2
1
1
1
1
2
2
1
1
2
2
EXPER
10
1
14
9
10
10
7
6
8
4
15
8
11
15
12
4
14
7
9
3
a) Appropriately code gender into a dummy variable
b) Run the simple regression 𝐼𝑛𝑐𝑜𝑚𝑒 = 𝛽0 + 𝛽1𝐺𝑒𝑛𝑑𝑒𝑟 + 𝜀
c) Give appropriate interpretation for intercept and slope coefficient in (b) above
d) Run the regression 𝐼𝑛𝑐𝑜𝑚𝑒 = 𝛽0 + 𝛽1𝑒𝑑𝑢𝑐 + 𝛽2𝑒𝑥𝑝𝑒𝑟 + 𝛽3𝐺𝑒𝑛𝑑𝑒𝑟 + 𝜀
Interpret the intercept, slope coefficients and the model fit.
Does this dataset provide credence to the assertion that “women are on average paid less than men”?
Q.4.
Discuss the concept of multi-criteria decision-making. Explain how multiple criteria can be incorporated into decision-making processes and discuss techniques such as weighted scoring, analytical hierarchy process (AHP), or TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution).
Q.5.
Discuss the concept of capital budgeting and its importance in investment decision-making. Explain how techniques such as net present value (NPV), internal rate of return (IRR), and profitability index (PI) can assist managers in evaluating and selecting investment projects.

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