Measure frequency of values in statplus how to#
Measure frequency of values in statplus series#

For example, if the value with the most decimal places is 6.1 and this is the smallest value, a convenient starting point is 6.05 (6.1 – 0.05 = 6.05). A convenient starting point is a lower value carried out to one more decimal place than the value with the most decimal places. Grouping data may not always have an intuitive way to do it or work out cleanly. For the class 30 – 39, the class midpoint = (30 + 39)/2 = 34.5.ĭepending on the format and precision of the data reported, we may have to decide how best to group our data into intervals, sometimes called bins or classes. The class midpoint is found by adding the lower limit and upper limit, then dividing by 2. For the class 30 – 39, the class width = 40 – 30 = 10. The class width is defined as the difference between consecutive lower class limits. 30 is known as the lower class limit, while 39 is the upper class limit. For example, if you had ages of adults from 20-69, it might make intuitive sense to group them as follows:Ĭonsider the 30-39 class. Some quantitative data, especially discrete, may only a contain a limited number of values and little thought would be needed in creating the frequency table. For example if you polled 20 kindergarteners on their favorite colors you could construct the following simple frequency table: Table 2.1: Frequency Table of Children’s favorite colors Color Displaying categorical data in a frequency table is fairly straightforward since you already have clearly defined categories. Once you have a set of data, you may first want to organize it to see the frequency, or how often each value occurs in the set.įrequency tables can be used to show either quantitative or categorical data. Frequency Tablesįrequency tables are a great starting place for summarizing and organizing your data. We will start by looking at a graphical method that can display any type of data, the frequency table. The emphasis will be on histograms and box plots.

Measure frequency of values in statplus series#

Some graphs that are used to summarize and organize Quantitative data are the dot plot, the histogram, the stem-and-leaf plot, the frequency polygon, the box plot, and the time series plot in special cases. Some of the types of graphs used to display Categorical data are pie charts and bar charts. The type of graph you choose to use first depends on the type of data you are working with. Statisticians often graph data first to get a picture of the data. Newspapers and the Internet use graphs to show trends and to enable readers to compare facts and figures quickly. A graph can be a more effective way of presenting data than a mass of numbers because we can see where data clusters and where there are only a few data values. These are tools that help you learn about the distribution, or shape of a sample or a population. Graphical descriptive methods consist of chart, tables, and graphs. Numerical descriptors consist of summary statistics, typically calculated from a sample, that represent important aspects such as the central tendency and variability of a distribution, or relative standing of a single observation with regards to the rest of the distribution.

Measure frequency of values in statplus how to#

You will learn how to construct and calculate, and even more importantly, how to interpret these measurements and graphs. We will look at both graphical and numerical descriptive methods. This area of statistics is called descriptive statistics.

In this chapter, you will study numerical and graphical ways to describe and display your data. Your agent might also provide you with a graph of the data. A better way might be to look at numerical descriptions such as the average or median house price. Looking at all the prices in the sample often is overwhelming. You may have no clue about the house prices, so you might ask your real estate agent to give you a sample data set of prices.

For example, suppose you are interested in buying a house in a particular area. Once you have collected data, what will you do with it? Data can be described and presented in many different formats.