Standard Scores

Sometimes we might need to compare one score to another. The comparison might involve scores from different instruments that have different means and standard deviations, or it might involve finding out the standing of a certain score in a group, or perhaps comparing a single score to the average. Usually this presents a problem, especially in the case of comparing two scores from two different instruments. But if we standardize…

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Measures of Variability (part 3)

Of the common measures of variability, range and mean deviation are both fairly useful for describing the spread of scores in a data set. But as we saw in the last two posts, both also have their problems. Because of this, by far the most often chosen measure of variability for describing a data set is standard deviation. Standard deviation, whose symbol is “s”, gives us a value that tells…

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Measures of Variability (part 2)

In the last post I introduced the simplest of measures of variability, that of range. Range has its problems, though, so it isn’t the method of choice in most cases. Mean deviation (or average deviation) is another type of variability measure. This one takes into consideration the distance the scores are from their own mean. A deviation is the mathematical difference (representing the distance) between any score and the mean…

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Measures of Variability (part 1)

Measures of variability (also called measures of dispersion) are values that show the dispersion of scores in a data set. In other words, variability shows how far apart the scores are in a distribution. A small measure of variability indicates that the scores are closer to the mean, while a larger measure of variability shows that the scores are further away from the mean. Variability is a measure of distance,…

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Measures of Central Tendency – The Mode

As we saw in the previous two posts, the mean and the median are used for continuous data, depending on normalcy of course, and these give us a midpoint for describing our data set. The mode can also be used with continuous data, and would simply be the value that occurs most often in the data set. But how do we judge the midpoint of the data when that data…

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Measures of Central Tendency – The Median

Out of the three measures of central tendency, the mean is the most common but it isn’t appropriate unless our data is normally distributed and continuous. What if we have continuous data, but it is skewed instead of normal? First, what is skewed data? When we think of normally distributed data, we might imagine the normal curve where most of the values are in the middle of the distribution with…

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Measures of Central Tendency – The Mean

Measures of central tendency are numerical values that give us the approximate midpoint of a data set. The three measures of central tendency are mean, median, and mode, and each is best suited for specific situations. In other words, they are descriptors that helps us to “sum up” the data set. For example, knowing the average amount of time children spend on homework would help you to judge whether your…

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Graphs and Charts and Tables, Oh My!

So you want to include a graph, chart, or table in your research report, but which one do you use? Is it just a matter of personal preference? Not exactly… The purpose of graphs, charts, and tables is to summarize information in an easy-to-understand way, but some types of data are better suited to graphs or charts, while more complicated or detailed information is better displayed in a table. Graphs…

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Scales of Measurement

“Scales of measurement” refers to how your variables are measured. For example, age is a continuous variable because there is no separation between one moment and the next as a person ages. But number of children in a family and gender are categorical variables because there is that separation. After all, no family has 1.5 children. Its either 1 child or 2 (or more, of course), and gender is self-explanatory.…

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Validity of an Instrument (part 2)

In the previous post, I talked about three types of validity: face validity, criterion-related, and content validity. And now for the rest of the story… A fourth type of validity is construct validity. This type is much more often used to validate instruments that measure abstract concepts, such as we tend to use in the social sciences. Suppose you write an instrument measuring self-esteem. Your task is to relate the…

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