Statistics Tutorial

The Study

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Getting StartedGeneral Instructions | Introduction to Your Study
Descriptive StatisticsHistograms | Scatter Plots | Central Tendency | Standard Deviation | Confidence Intervals
Relating VariablesCorrelation
Important ConceptsThe Normal Distribution | Z Scores | Probability Distributions
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Explanation

Introduction to Your Study
Throughout this tutorial, we will use real data from a real experiment to illustrate the topics that you will learn about.

Procedures used in the selection of employees must be job-related, that is, they must provide accurate information about which candidates are likely to perform better on the job to be filled. This is not a new concept. Merit principles and job-relatedness have been long-standing requirements in most public sector selection systems. Statistics,e.g.,the mean, standard deviation and correlation coefficient combined with graphical displays such as histograms, frequency distributions and scatter plots can give us a wealth of information about the accuracy, consistency and defensibility of our selection procedures.

We will use the vocabulary of statistics, which can be confusing if you haven't seen it before, so here is an introduction to the study you will be working through and the words that are used to describe it.

The Data
Statistics are designed to help us understand things we observe in the world around us. To use statistics, we have to measure things in the real world and so produce data. Data can be expressed as words or numbers, and are plural - so you say "Here are my data."

So that we know which aspects of the data we are talking about, we use the following words:

  • To generate data we take measurements or make observations of specific qualities of things;
  • The things we are measuring are called the experimental units of the study. They might be referred to as 'people' or 'soil samples', whatever is being measured, but in this study, they are referred to as people;
  • The qualities that we measure, or observe, are called variables. So if you measured a piece of string, the string would be the experimental unit and 'length' would be the variable;
  • All variables take a range of values - the variable 'length' might take the values 3 or 10.5, for example. Generally, one measurement of a variable from a single experimental unit will produce a single value. If we say "Length = 5" then 'length' is the variable and '5' is the value.

Your study measured two variables: Written, measured in points and Performance Rating, measured in points

The Study
Your study is looking for a relationship between two variables. You want to know if, and how strongly performance rating and written are related.

Exploration

Here is the data from your study. Hover over the hightlighted parts of the table to find out how they relate to the description above.
Written (points)Performance Rating (points)
90100
6084
4872
9672
6084
4860
9684
6190
4060
7272
10090
8460
7248
7296
8460
6048
8496
3636
9696
8484
3636
6060
1212
2424
3636
2424
7272
4848

Application

Let's look at your data now and check that you have understood the concepts described above.
We are measuring written and performance rating in your data. Which of the words in the box to the left best describes written and performance rating?   Help
Read the sentence below and label the bold words
The first written measured is 90 points
Which of these words best describes written?   Help
Which of these words best describes 90?   Help
Instructions | Frequency Histograms