BUS 308 Statistics for Managers

Name: BUS 308 Statistics for Managers
Brand: Ashford University
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Author: Leah Howard

A solved assignment on statistical methods for business management.

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Running Head: What I’ve learned about Statistics
Debra Johnson
What I’ve learned about Statistics
BUS 308 Statistics for Managers
Instructor: Travis Hayes
February 18, 2025
Reflecting on your experience in the course "Statistics for Managers," what key concepts or
techniques have you learned about descriptive statistics, particularly in relation to measures of
central tendency? Discuss the importance of these concepts in decision-making and their
application in real-world business contexts. In your response, include examples of how these
statistical methods can be used to analyze data effectively. Your answer should be between 600-
800 words.

What I’ve learned about Statistics Page 2
Introduction
The process of data analysis is that of turning data into significant information. While
there are no hard and fast distinctions for analyzing statistical data, ensuring that you have a
methodical approach is vital to an accurate analysis. Transforming data into statistical
information and then communicating it accurately is a crucial dynamic of effective decision
making. Once a policy has been implemented, it is necessary to monitor and evaluate the
effectiveness of that policy. As Othman (2005) states, ‘Good statistics, therefore, represent a key
role in good policy making.” The impact of policy can be measured with good statistics.
I.
Descriptive Statistics
In the single factor tests and analysis we have a limitation to choose only one factor for
comparison which often fails. In reality, more than one factor may influence the outcome and
comparison of phenomena by including all those factors in a model giving an accurate degree of
comparison. Multiple regression is one such technique in which we can include control
variables, and as many as possible. We can test the impact of their inclusion, and there is a
chance of eliminating the non-significant variables to fit the accurate model. (Hoffmann, 1981).
A. Measures of Central Tendency. We start thinking about how we can represent a set of
numbers with one number that somehow represents the "center". We can then talk about the
differences between populations, samples, parameters and statistics. A measure of central
tendency is a single value that attempts to describe a set of data by identifying the central
position within that set of data. As such, measures of central tendency are sometimes called
measures of central location. They are also classed as summary statistics. The mean (often called

What I’ve learned about Statistics Page 3
the average) is most likely the measure of central tendency that we are most familiar with, but
there are others, such as the median and the mode. (Lund & Lund, 2013).
The mean, median and mode are all valid measures of central tendency, but under
different conditions, some measures of central tendency become more appropriate to use than
others. In the following sections, we will look at the mean, mode and median, and learn how to
calculate them and under what conditions they are most appropriate to be used. (Lund & Lund,
2013).
The Mean (Arithmetic). The mean (or average) is the most popular and well known
measure of central tendency. It can be used with both discrete and continuous data, although its
use is most often with continuous data. The mean is equal to the sum of all the values in the data
set divided by the number of values in the data set. If we have n values in a data set and they
have values x1, x2, ..., xn, the sample mean, usually denoted by (pronounced x bar), is:
(Lund & Lund, 2013).
This formula is usually written in a slightly different manner using the Greek capitol
letter, pronounced "sigma", which means "sum of...” (Lund & Lund, 2013).
In statistics, samples and populations have very different meanings and these differences
are very important, even if, in the case of the mean, they are calculated in the same way. To
calculate the population mean and not the sample mean; use the Greek lower case letter "mu",
denoted as μ: (Lund & Lund, 2013).
The mean is essentially a model of the data set. It is the value that is most common. The
mean is not often one of the actual values observed in a data set. One of its important properties

What I’ve learned about Statistics Page 4
is that it minimizes error in the prediction of any one value in a data set. That is, it is the value
that produces the lowest amount of error from all other values in the data set An important
property of the mean is that it includes every value in a data set as part of the calculation. In
addition, the mean is the only measure of central tendency where the sum of the deviations of
each value from the mean is always zero. (Lund & Lund, 2013).
The Median. We usually prefer the median over the mean (or mode) when our
data is skewed (i.e., the frequency distribution for our data is skewed). If we consider the normal
distribution - as this is the most frequently assessed in statistics - when the data is perfectly
normal, the mean, median and mode are identical. They all represent the most typical value in
the data set. But as the data becomes skewed the mean loses its ability to provide the best central
location for the data because the skewed data is dragging it away from the typical value.
However, the median best retains this position and is not as strongly influenced by the skewed
values. (Lund & Lund, 2013).
The median is the middle score for a set of data that has been arranged in order of
magnitude. The median is less affected by outliers and skewed data. In order to calculate the
median, suppose we have the data below:
65 55 89 56 35 14 56 55 87 45 92
We first need to rearrange that data into order of magnitude (smallest first):
14 35 45 55 55 56 56 65 87 89 92
(Lund & Lund, 2013).
Our median mark is the middle mark - in this case, 56. It is the middle mark because
there are 5 scores before it and 5 scores after it. This works fine when you have an odd number
of scores, but what happens when you have an even number of scores? What if you had only 10

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Ashford University

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Statistics

BUS 308 Statistics for Managers

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