HI6007 Statistics for Business Decisions: Holmes Institute Group Work

This assignment solution covers key statistical concepts applied to business decisions. It includes frequency distribution analysis, hypothesis testing, and regression analysis. Specifically, it addresses questions related to furniture order values, the relationship between unit price and demand, and the significance of advertising spots on sales. The solution involves calculations and interpretations using statistical tools, offering insights into data analysis and decision-making processes. The document also includes an estimated regression equation and related computations. The assignment was prepared by a student and is available on Desklib, a platform providing study tools and resources for students.

Running head: STATISTICS FOR BUSINESS DECISIONS
Statistics for Business Decisions
Name of the Student:
Name of the University:
Author’s Note:
Course ID:

1STATISTICS FOR BUSINESS DECISIONS
Table of Contents
Question 1:.......................................................................................................................................2
Answer to Part a:.........................................................................................................................2
Answer to Part b:.........................................................................................................................2
Answer to Part c:.........................................................................................................................3
Question 2:.......................................................................................................................................3
Answer to Part a:.........................................................................................................................3
Answer to Part b:.........................................................................................................................3
Answer to Part c:.........................................................................................................................4
Question 3:.......................................................................................................................................4
Question 4:.......................................................................................................................................5
Answer to Part a:.........................................................................................................................5
Answer to Part b:.........................................................................................................................5
Answer to Part c:.........................................................................................................................5
Answer to Part d:.........................................................................................................................6
Answer to Part e:.........................................................................................................................6
References and bibliographies:........................................................................................................7

2STATISTICS FOR BUSINESS DECISIONS
Question 1:
Answer to Part a:
Answer to Part b:
100-
149 150-
199 200-
249 250-
299 300-
349 350-
399 400-
449 450-
499
-
5
10
15
20
25
30
35
6
30 28
12
6 8 6 4
Furnititure Order Values
Percent Frequency
Distribution
In accordance with the above figure, it could be stated that the distribution is rightly
skewed, since fewer data plots could be observed on its right side. The mean is pulled typically
towards the tail, which implies that it is higher than the median value (Anderson et al., 2014).

3STATISTICS FOR BUSINESS DECISIONS
Answer to Part c:
As the shape of the distribution is found to be rightly skewed, the mean value is expected
to exceed the median value, since the graph tail is pulled towards greater positive numbers
(Anderson, Sweeney & Williams, 2014). Therefore, the best measure of location for the data set
is median, since it would help in identifying those values, which are above and below 50% of the
furniture orders.
Question 2:
Answer to Part a:
From the above tables, t-stat is obtained as -8.617 and p-value is 0.000, which is below
0.05 level. This rejects the null hypothesis of the regression coefficient, which is zero (Cressie,
2015). Therefore, it could be inferred that relationship exists between unit price and demand.
Answer to Part b:

4STATISTICS FOR BUSINESS DECISIONS
From the above table, the coefficient of determination is obtained as 0.617, which
signifies that 61.7% of variance in the variable demand is described by the variable unit price
(Granger, 2014).
Answer to Part c:
The coefficient of correlation is computed through square root of the coefficient of
determination (Hair Jr et al., 2015). The value obtained is 0.786, which implies that strong
correlation exists between demand and unit price.
Question 3:
Null hypothesis, H0: No difference exists among the means of the three populations
Alternative hypothesis, H1: Significant difference exists among the means of the three
populations
In this case, α is provided as 0.05 and the significance F or p-value is obtained as 0.00.
This denotes the rejection of null hypothesis, as it is lower than 0.05 (Liu, 2017). As a result,

5STATISTICS FOR BUSINESS DECISIONS
alternative hypothesis would be accepted and therefore, it could be inferred that significant
difference exists among the means of the three populations.
Question 4:
Answer to Part a:
The estimated regression equation is presented as follows:
Y = 0.8051 + 0.4977X1 + 0.4733X2
Answer to Part b:
The above table clearly denotes that significant relationship is present between the
dependent and independent variables since p-value is lower than 0.05 at 95% confidence
interval.
Answer to Part c:
The t-value at 95% confidence interval with degrees of freedom as 13 is 2.16 (Sekaran &
Bougie, 2016). Since t-stat is less than the tabulated value for X1, it is almost identical to zero.

6STATISTICS FOR BUSINESS DECISIONS
On the other hand, since t-stat for X2 is more compared to the tabulated value, it could be said
that the advertising spot value is not close to zero at all.
Answer to Part d:
When there is no change in price level, a rise in advertising spot per unit (X2) would lead
to increase in the sale of mobile phone by 0.4733 per unit.
Answer to Part e:
Price per unit for X1 = $1,000
Price charged = $20,000
Quantity sold = $20,000/$1,000 = $20
Advertising spots = 10
Y = 0.8051 + 0.4977X1 + 0.4733X2
Y = 0.8051 + (0.4977 x 20) + (0.4733 x 10)
Y = 16
Therefore, the company could expect to sell 16 mobile phones per day.

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References and bibliographies:
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J.
(2014). Essentials of statistics for business and economics. Cengage Learning.
Anderson, D., Sweeney, D., & Williams, T. (2014). Modern business statistics with Microsoft
Excel. Nelson Education.
Cressie, N. (2015). Statistics for spatial data. John Wiley & Sons.
Granger, C. W. J. (2014). Forecasting in business and economics. Academic Press.
Hair Jr, J. F., Wolfinbarger, M., Money, A. H., Samouel, P., & Page, M. J. (2015). Essentials of
business research methods. Routledge.
Liu, Z. (2017). Teaching reform of business statistics in college and university. EURASIA
Journal of Mathematics, Science and Technology Education, 13(10), 6901-6907.
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach.
John Wiley & Sons.
Siegel, A. (2016). Practical business statistics. Academic Press.
Stine, R., & Foster, D. (2017). Statistics for Business: Decision Making and. Addison-Wesley
SOFTWARE-JMP.