graphs in stats

Suppose that you have two sets of data to work with. The first set is a list of all the injuries that were seen in a clinic in a month’s time. The second set contains data on the number of minutes that each patient spent in the waiting room of a doctor’s office. You can make assumptions about other information or variables that are included in each data set.

For each data set, propose your idea of how best to represent the key information. To organize your data would you choose to use a frequency table, a cumulative frequency table, or a relative frequency table? Why?

What type of graph would you use to display the organized data from each frequency distribution? What would be shown on each of the axes for each graph?

Requirements for this post:

  • OpenStax Book: Chapter 2—Section 2.1
  • Lesson
  • Minimum of 1 scholarly source

Here is the OpenStax Book: Chapter 2—Section 2.1

  • Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs

    One simple graph, the stem-and-leaf graph or stemplot, comes from the field of exploratory data analysis. It is a good choice when the data sets are small. To create the plot, divide each observation of data into a stem and a leaf. The leaf consists of a final significant digit. For example, 23 has stem two and leaf three. The number 432 has stem 43 and leaf two. Likewise, the number 5,432 has stem 543 and leaf two. The decimal 9.3 has stem nine and leaf three. Write the stems in a vertical line from smallest to largest. Draw a vertical line to the right of the stems. Then write the leaves in increasing order next to their corresponding stem.

    EXAMPLE 2.1

    For Susan Dean’s spring pre-calculus class, scores for the first exam were as follows (smallest to largest):

    33; 42; 49; 49; 53; 55; 55; 61; 63; 67; 68; 68; 69; 69; 72; 73; 74; 78; 80; 83; 88; 88; 88; 90; 92; 94; 94; 94; 94; 96; 100

    Stem Leaf
    3 3
    4 2 9 9
    5 3 5 5
    6 1 3 7 8 8 9 9
    7 2 3 4 8
    8 0 3 8 8 8
    9 0 2 4 4 4 4 6
    10 0
    Stem-and-Leaf Graph

    The stemplot shows that most scores fell in the 60s, 70s, 80s, and 90s. Eight out of the 31 scores or approximately 26%






    were in the 90s or 100, a fairly high number of As.

    TRY IT
    For the Park City basketball team, scores for the last 30 games were as follows (smallest to largest):

    32; 32; 33; 34; 38; 40; 42; 42; 43; 44; 46; 47; 47; 48; 48; 48; 49; 50; 50; 51; 52; 52; 52; 53; 54; 56; 57; 57; 60; 61

    Construct a stem plot for the data.

    The stemplot is a quick way to graph data and gives an exact picture of the data. You want to look for an overall pattern and any outliers. An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500) while others may indicate that something unusual is happening. It takes some background information to explain outliers, so we will cover them in more detail later.

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