Learning Outcome PPT for the Course Assignment

Running Head: MERGING AND ACQUISITION 1

MERGING AND ACQUISITION 2

MERGING AND ACQUISITION

NAME:

INSTRUCTOR:

DATE:

Merging and Acquisition

Introduction

Some of the factors determining merger and acquisition activities in retailing were examined in this paper to aid in decision making that have a positive impact on a firm. Characteristics of firms that were targeted for acquisition and the firms that were willing to make acquisition were looked into. Growth rate of sales for target firms and bidders were tested to enable management make decision wisely on acquisition (Christofi et al., 2017).

Growth rate of sales for target firms

The growth rate of sales for firms targeted for acquisition was tested using normal distribution tests. A sample of 25 firms was collected for this study. The mean sales growth rate was 0.16 and the standard deviation was 0.12. These are required in order to test for normally distributed data (D’Agostino, 2017). We perform t-test since the only sample statistics were known (Emmert-Streib & Dehmer, 2019).

The research question for this study will be: Is there statistical significant difference between the population mean and sample mean for sales growth rate of target firms? The hypothesis testing process was as given below;

Hypotheses

The following are the null and alternative hypotheses.

H0: μ = .10. The mean growth rate of sales for target firms is not different from 10%

Ha: μ >.10. The mean growth rate of sales foe target firms exceeds 10%.

Test statistics

T-test was carried out to examine whether the sales growth rate of 0.16 was indeed statistically significant different from the 0.10.

The t-test is given as;

t =

= = 2.50

Calculate the degrees of freedom by 1 from the sample size (Sung & Han, 2018);

df = 25 – 1 = 24

Determine the critical value from the t table at α = 0.10, 0.05, 0.01 and 0.001.

For α = 0.10, tα = 1.318 which is less than the calculated value of t = 2.50 implying we reject the null hypothesis at α = 0.10 and conclude Ha: μ >.10.

For α = 0.05, tα = 1.711 which is less than the calculated value of t = 2.50 implying we reject the null hypothesis at α = 0.05 and conclude Ha: μ >.10.

For α = 0.01, tα = 2.492 which is less than the calculated value of t = 2.50 implying we reject the null hypothesis at α = 0.01 and conclude Ha: μ >.10.

For α = 0.001, tα = 3.467 which is less than the calculated value of t = 2.50 implying we fail to reject the null hypothesis at α = 0.001 and conclude Ha: μ =.10.

Decision

There was very strong evidence to reject the null hypothesis at α = 0.01 and we conclude that the mean growth rate of sales for target firms exceeds 10% (Bowerman et al., 2019).

Growth rate of sales for bidders

The growth rate for firms that were willing to make acquisition was examined in order to come up with decisions regarding acquisition. A sample size of 25 firms was collected for analysis necessary for decision making. The mean growth rate of sales was 0.12 and the standard deviation was 0.09. We perform t-test since the only sample statistics were known;

Hypotheses Tested

Hypotheses to be tested;

H0: μ = .10. The mean growth rate of sales for bidders is not different from 10%

Ha: μ >.10. The mean growth rate of sales foe bidders exceeds 10%.

Test statistics

T-test was carried out to examine whether the sales growth rate of 0.12 was indeed statistically significant different from the 0.10.

The t-test formula is given as follows;

t =

= = 1.111

Calculate the degrees of freedom by 1 from the sample size;

= 25 – 1 = 24

Determine the critical value from the t table at α = 0.10, 0.05, 0.01 and 0.001.

For α = 0.10, tα = 1.318 which is greater than the calculated value of t = 1.111 implying we fail to reject the null hypothesis at α = 0.10 and conclude Ha: μ = .10 (Trafimow, & Earp, 2017).

For α = 0.05, tα = 1.711 which is greater than the calculated value of t = 1.111 implying we fail to reject the null hypothesis at α = 0.10 and conclude Ha: μ = .10.

For α = 0.01, tα = 2.492 which is greater than the calculated value of t = 1.111 implying we fail to reject the null hypothesis at α = 0.10 and conclude Ha: μ = .10.

For α = 0.001, tα = 3.467 which is greater than the calculated value of t = 1.111 implying we fail to reject the null hypothesis at α = 0.10 and conclude Ha: μ = .10.

Decision

We failed to reject the null hypothesis at α = 0.10 and conclude that there was extremely evidence that the mean growth rate of sales for bidders did NOT exceed 10%.

Conclusion

Analysis shows that the growth of sales for firms targeted for acquisition exceeded 10% but the firms that were willing to place bids for acquisition had sales growth rate not exceeding 10%. The bidding firms should be analyzed critically to ensure they meet the requirements of acquiring the already existing firms that have great growth rate curves.

Reference

Christofi, M., Leonidou, E., & Vrontis, D. (2017). Marketing research on mergers and acquisitions: a systematic review and future directions. International Marketing Review.

D’Agostino, R. B. (2017). Tests for the normal distribution. In Goodness-of-fit techniques (pp. 367-420). Routledge.

Emmert-Streib, F., & Dehmer, M. (2019). Understanding statistical hypothesis Testing: the logic of statistical inference. Machine Learning and Knowledge Extraction, 1(3), 945-961.

Bowerman, B., Drougas, A. M., Duckworth, A. G., Hummel, R. M. Moniger, K. B., & Schur, P. J.  (2019). Business statistics and analytics in practice (9th ed.). McGraw-Hill

ISBN 9781260187496

Sung, W. P., & Han, T. Y. (Eds.). (2018, July). Exploration and Practice of a New Formula for Calculating the Degree of Freedom. In MATEC Web of Conferences (Vol. 175, p. 03018). EDP Sciences.

Trafimow, D., & Earp, B. D. (2017). Null hypothesis significance testing and Type I error: The domain problem. New Ideas in Psychology, 45, 19-27.