Tip:
Highlight text to annotate it
X
Welcome to Week 4 of STAT 280. This week we finish studying descriptive statistics as
we focus on creating and understanding various types of charts.
As usual, there are two discussion topics this week. As a minimum, respond to the first
discussion topic regarding charts. The second discussion topic, asks you to identify the
muddiest or least understood point in this week's textbook assignment. Respond to this
topic if appropriate. However, please follow the postings of others and, if you can, clarify
muddy points identified by other students.
A chart or graph is a visual representation of a set of data. It generally takes the form
of a two-dimensional figure such as a histogram, scatterplot, or bar graph. There are also
three-dimensional graphs available, which can be useful in multivariate statistical analysis.
There are three categories of charts. The first category uses Cartesian coordinates.
Such charts are useful in showing relationships between variables. This type of chart typically
uses two axes: a horizontal x-axis and a vertical y-axis. The point where they meet is its origin,
identified as the ordered pair (0, 0). The second category of chart is the pie chart,
good for showing how a whole is divided up. For example, one would use a pie chart to
show how your total budget is divided among various expense categories. Finally, the third
category is the bar or column chart, useful for showing how different categories compare
to each other. For example, how total revenue compares across three different years.
Your textbook reading assignment this week will describe several types of charts and
show you step-by-step how to create each type using Microsoft Excel.
Charts created in Microsoft Excel are dynamic, which means they will update when you make
changes to the underlying data.
A chart of particular interest to statisticians is the histogram. The histogram is the most
commonly used graph to display frequency distributions. Later in this course we will learn how to
use the histogram to evaluate normality. This becomes very important in hypothesis testing,
as the hypothesis test you select to analyze your data is, in large part, determined by
whether or not your data is normally distributed.
You see here a picture of a histogram. It includes 103 cases, which represent high school
students. The x-axis reflects grade point average or GPA. The y-axis reflects frequency
counts. As you can see in this example, the histogram consists simply of a set of vertical
bars or bins with no space between bins. Values of the variable being studied are measured
on a continuous scale along the horizontal x-axis, in this case GPA. The bins are of
equal width or class interval, and the height of each bin corresponds to the frequency of
the class interval it represents. As you can see, most students in the sample have a GPA
between 2.25 and 2.5. In fact, 20 students have a GPA in this class interval as indicated
by the y-axis. The histogram is used to graphically portray data that are measured on an interval
or ratio scale.
The total area of the histogram is equal to the number of cases. Since this histogram
represents 103 cases, 103 represents the sum of the height of all the bins added together.
The written assignment this week involves creating a histogram using Microsoft Excel.
Follow the step-by-step instructions and example provided in the textbook for this assignment.
There is also a quiz consisting of 10 multiple-choice items that you must complete this week.
Let's close this week's video with a prayer as usual:
Loving Father, I stand before You in the midst of confusion and uncertainties. Give me, O
Lord, the vision to see the path to truth, Your truth. Grant me the courage to follow
Your way, that through the gifts and talents You have given me, I may bring Your life and
Your love to others and that the veil of uncertainty be lifted from me. I ask this through Our
Lord, Jesus Christ. Amen