Statistics Homework: Data Analysis, Probability, and Formulas

This statistics homework assignment covers a range of topics, including data collection methods, analysis of numerical data using measures like arithmetic mean and median, and calculations involving percentages. It delves into probability calculations, such as determining the probability of an event and identifying modal groups. The assignment also explores financial formulas, including compound interest calculations. Furthermore, it examines statistical concepts like Z-scores and confidence intervals. Finally, the assignment analyzes the relationship between advertising expenditure and sales, using data to illustrate and predict future trends. The assignment provides a comprehensive overview of key statistical concepts and their application in real-world scenarios. Students can find the complete solution on Desklib, a platform offering valuable study resources.

Undergraduate Modular
Scheme Examination

TABLE OF CONTENTS
QUESTION 1...................................................................................................................................3
A..................................................................................................................................................3
B..................................................................................................................................................3
C..................................................................................................................................................4
D..................................................................................................................................................4
QUESTION 2...................................................................................................................................4
A..................................................................................................................................................4
B..................................................................................................................................................4
C..................................................................................................................................................4
D..................................................................................................................................................5
E..................................................................................................................................................5
QUESTION 3...................................................................................................................................5
A..................................................................................................................................................5
B..................................................................................................................................................5
C..................................................................................................................................................5
QUESTION 4...................................................................................................................................5
A..................................................................................................................................................5
B..................................................................................................................................................6
C..................................................................................................................................................6
REFERENCES................................................................................................................................7

QUESTION 1
A
The data collection is being referred to as different methods through which data can be
gathered. The primary data source includes three major techniques which are as follows-
 Interview
 Experiment
 Field observation
On the other hand, the three different secondary sources of data include the following-
 Journals
 Online websites
 Government records
B
Date Tesco stock price
1/5/2019 220
1/6/2019 224.1
1/7/2019 220.7
1/8/2019 216.6
1/9/2019 238.2
1/10/2019 232.5
1/11/2019 229.4
1/12/2019 255.2
1/1/2020 246.9
1/2/2020 228.5
1/3/2020 228.8
1/4/2020 218.8
3/4/2020 223.9
Arithmetic mean 229.508
Median 228.5
Monthly percentage change on
01/04/2020 -0.0437

C
D
It is not true that primary data is qualitative data because it can include both the
information that is based on facts and figures and other non- numeric information as well
(Johnson and Berenson, 2019). this is very important for the reason that the primary data can also
involve asking questions which relates to the numeric information and facts and figures as well.
QUESTION 2
A
The probability of spending over £10 weekly is 0.10 because 19
= 19/ 185
= 0.10
B
Frequency of people living 1 mile away from the campus
= (10 + 20 + 19) / 185
= 49/ 185
=0.26
C
The modal group is the one which has the majority of frequency being present. So out of
all the category of amount the class which is having maximum frequency will be the modal class

(Taylor, 2018). Hence, the modal group with the table is amount spent 5.00- 9.99. this is because
of the reason that is includes the maximum frequency which is 77 (18 + 39 + 20).
D
Formula
A= P (1 + rt)
A= 200 (1 + (0.03 * 3))
A = 218
E
Formula
A = P (1 + r/n) n/t
A= 218.55
QUESTION 3
A
Z score= (X - μ) / σ
= (70% - 70) / 10
= -6.93
B
The confidence interval for the 95 % in case of the test score involves 1.96 and this
simply states that there is 1.96 chance that the person will get the marks necessary to secure in
the interview.
C
= 6/ 24
= 0.25
QUESTION 4
A
With the help of the above chart it is clear that there is a statistical relation being present
in both the variable that is sales and advertising expenditure. This outlines the fact that the
variables are not much deviating and mostly constant as they are near to the trend line. This

simply implies that the working of company is in accordance to the trend line and is beneficial
for the company.
The different characteristic of the relationship outlined are as follows-
 There are two different variables that is one dependent and one independent wherein
sales is dependent and advertising expense is independent.
 Another characteristic outlined within the study was that any change in independent
variable will cause a change in dependent variable (Nielsen, 2018). For example, decline
in expenses from 12 to 11 resulted in decline in sales 40 to 29.
 Another characteristic is that this relationship is also used in order to forecast and predict
the future data as well and assist in effective decision making.
B
The equation relating to the relationship between advertising expenditure and sales is as
follows-
Y= -0.509 x + 32.8
With the help of the above equation the company can predict the future expense and sales as
well.
C
There is a relation being present between both the variables that is advertising
expenditure and the sales of the company. with the help of the data it is clear that when expenses
are increased then sales are also increased and when expenses are reduced then the sales are also
reduced (Anderson and et.al., 2020). For example, in the year 2012 the expense was 14 and in
2013 it declined to 3. Similarly, in case of sales for 2012 it was 43 and with decline in expense
the sales also declined to 17. This clearly explains the fact that there is a relation being present in
both the variable.
The recommendation for the future development to the manager is to constantly work on
the advertising and marketing so that the sales of the company is increasing. This is necessary for
the reason that when the marketing will be improved then more people will be knowing about the
company and ultimately the sales will be increased.

REFERENCES
Books and Journals
Anderson, D. R. and et.al., 2020. Essentials of modern business statistics with Microsoft Excel.
Cengage Learning.
Johnson, M. E. and Berenson, M. L., 2019. Choosing among computational software tools to
enhance learning in introductory business statistics. Decision sciences journal of
innovative education. 17(3). pp.214-238.
Nielsen, P. B., 2018. The puzzle of measuring global value chains–The business statistics
perspective. International economics. 153. pp.69-79.
Taylor, S., 2018. Business statistics: for non-mathematicians. Bloomsbury Publishing.