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The field of statistics can be broken down into two broad categories, descriptive statistics and inferential statistics.

The basic taxonomy of the field of statistics looks like this:

- Descriptive Statistics
- Inferential Statistics
**Estimation Statistics**- Confidence Intervals
- Parameter Estimation

**Hypothesis Testing**

Descriptive statistics allow a researcher to describe or summarize their data. For example, descriptive statistics for a study using human subjects might include the sample size, mean age of participants, percentage of males and females, range of scores on a study measure, etc.. Descriptive statistics are often briefly presented at the beginning of the Results chapter.

Inferential statistics are usually the most important part of a dissertation's statistical analysis. Inferential statistics are used to allow a researcher to make statistical inferences, that is draw conclusions about the study population based upon the sample data. Most of your dissertation results chapter will focus on presenting the results of inferential statistics used for your data.

There are two main types of Inferential Statistics, estimation and hypothesis testing.

Estimation statistics are used to make estimates about population values based on sample data. There are two type of estimation statistics, confidence intervals and parameter estimation.

These statistics allow us to establish a range that has a known probability of capturing the true population value. There are many different confidence interval formulas, for example for estimating the population mean, or the percentage of a characteristic in the population.

Parameter estimation statistics allow us to make inferences about how well a particular model might describe the relationship between variables in a population. Examples of parameter estimation statistics include a linear regression model, a logistic regression model, and the Cox regression model. For more information, see my Statistics Tutorial topics on Linear Regression and Multiple Linear Regression.

Hypothesis testing statistics allow us to use Statistical Data Analysis to make statistical inferences about whether or not the data we gathered support a particular hypothesis. There are many hypothesis testing procedures. See my Statistics Tutorial topics on some of these such as the T-Test, Chi-Square, and ANOVA (analysis of variance).

When you hire me to consult/advise/tutor you, I will also provide a written narrative report that demonstrates how to report the statistical aspects of your dissertation, I will provide you with written samples of how the statistics should be presented, in your dissertation proposal, or in your dissertation results section. I also provide readily available statistics help by phone and email to ensure that you understand all of the statistics that I used for your study so that you can confidently defend your results (except in the event of my incapacitation, death or the demise of my business).

For more information see FAQ About Statistical Consulting and Other Statistics Resources.

Simply contact me by phone or email to get started.

Steve Creech

1-800-357-0321 or 1-630-936-4771 | Steve@StatisticallySignificantConsulting.com

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