## The Study

 Getting Started General Instructions | Introduction to Your Study | Experimental Design | Stating a Hypothesis Descriptive Statistics Histograms | Central Tendency | Standard Deviation | Confidence Intervals Comparing Two Samples Samples and Populations | Choosing a T-Test | Independent T-Test | P-Values and T-Tables Important Concepts The Normal Distribution | Z Scores | Probability Distributions Levels You are currently on Introduction to Your Study at level 1. Level 1 | Level 2 | Level 3 Next Topic Instructions | Experimental Design

### Explanation

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

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 students;
• 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.

The Study
Experiments often compare one set of measurements with another. The two sets of measurements could differ because they were each taken from different groups of experimental units, or because they were taken from the same experimental units under two different conditions. Each set of measurements is called a sample. Your study splits the students into two samples:

• The sms2 sample
• The sms1 sample

Such studies always have two variables, each with its own role to play. They are:

• The independent variable discriminates between the two samples. Your independent variable is smstreatment and it can take one of two values: sms2 or sms1.
• The dependent variable is whatever you are measuring in each sample. In the case of this study, the dependent variable is dailyreading, so you expect dailyreading to differ depending on smstreatment (whether it is sms2 or sms1).

Such studies have an idea they wish to test. The idea is called the hypothesis. Each study actually has two versions of the hypothesis - one that says there is a difference between the two samples (the experimental hypothesis) and one that says that there is no difference (this is called the null hypothesis).

• The experimental hypothesis in this study is sms treatment will increase motivation.
• The null hypothesis in this study is sms treatment will not increase motivation.
There is a page later in this tutorial that explains hypotheses in full.

### 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.

The table below shows dailyreading for the both the sms2 and the sms1 samples.
Sms2Sms1
3
4
6
3
3
4
1
5
3
4
3
3
2
4
3
6
3
4
2
3
3
4
3
6
3
3
5
3
5
3
5
3
4
5
1
3
3
6
3
3

### Application

Let's look at your data now and check that you have understood the concepts described above.
We are measuring dailyreading in your data. Which of the words in the box to the right best describes the role of dailyreading?
SMStreatment can be either sms2 or sms1. What do these two words refer to?
Which of these is your null hypothesis?
Which variable is the independent variable?
Which variable is the dependent variable?
Imagine that you measured dailyreading from a student in the sms2 sample and got a value of 6 opinion.
Which of these words best describes dailyreading?
Which of these words best describes sms2?
Which of these words best describes 6?
 Instructions | Experimental Design