Statistics Research Design

Welcome to www.educator.com.0000

Today we are going to be talking about research designs, also known as research strategies0002

Here is the roadmap for today.0007

First we have been talking about descriptive versus inferential statistics.0010

You now that now were talking about different ways of doing inferential statistics so we are just going to review this again.0015

Then we are going to talk about variables in relationships.0021

There are different kinds of variables and different kinds of relationships you need to know about.0025

We are going to introduce three different categories of research strategies or designs0029

and then we are talking about why cannot other strategies besides the experimental strategy determine causation.0035

We are going to talk about what is so special about experiments.0042

Finally, we are going to end with some experimental terminology.0046

Now that we have been doing a lot of descriptive statistics so far looking at visualizing data, summarizing it,0050

and we could do that for both one and two variables.0059

Then we talked about why inferential statistics is different.0062

Number 1, we are interested in generalization and because of that we covered some sampling methods that allow our samples to generalize to the population.0066

We also introduced the idea that we would like to have comparison in order to examine causation.0077

We would like to know whether one variable causes another not just the relationship between them in terms of a regression line0085

but we like to know does one cause the other one.0093

In order to do that, we are going to have to learn about experiments.0098

But before we learn about experiments, it is going to be helpful to learn about other kinds of research strategies in addition to experiments,0103

just so we could see why experiments are so special and different.0112

but in order to understand those different kinds of research strategies we are going to need to review variables and the relationship that they can have.0117

One thing you need to know about variables is that we have covered 2 broad kinds of variables so far.0125

Categorical, categories as the variable levels instead of actual numerical values or continuous0132

where the values of the variables are numbers that are meaningful in some way.0144

An example of categorical variables are whether kids have pets or not, versus continuous which might be something like a score on a biology test.0149

Then you can have maybe 1 – 100 and each of those numbers are meaningful.0163

In terms of relationships, there is a bunch of different relationships we actually covered.0169

All of those relationships so far have been descriptive relationships.0175

We have covered relationship such as linear relationship, curvilinear, we have also looked0180

at relationships such as negative correlation and positive correlation.0188

But all of those relationships are descriptive.0199

They are just describing what the relationship is like.0204

They are not actually telling you whether one variable causes the other variable.0208

Those are causal relationships.0213

They are not necessarily telling you that one variable does not cause the other one either.0215

This is a new kind of relationship that we are going to be looking at.0219

Only one kind of study, what kind of research design can actually look at causal relationships.0224

And that is going to be through the experimental research strategy or design.0234

This is the only one.0245

That one is pretty special.0248

So far we have only covered these other kinds of relationships.0251

Before we go on to the nitty-gritty of an experiment, it helps to know what are the non-experiment.0255

Not every type of research study is an experiment just because you collect data and some variables does not mean you have an experiment.0266

That is a very meaning to start using a mere context.0276

A lot of people especially in the media or popular press they only use it in a more loose way before they call it an experiment.0280