# 1. Introducing Statistics

Learn about Excel's in-built statistics functions and how to install the Analysis Toolpack add-in, which contains some additional statistical tools.

**Introducing statistics**

- **Descriptive** statistics are used when you have access to all of the population data

- **Inferential** statistics are used when you are analysing a sample and inferring conclusions from that sample for a larger population

- **This course will focus solely on descriptive statstics**

**Installing the analysis toolpak**

**1** Go to the file tab and go to 'Options'

**2** Select 'Add-ins' on the left-hand menu

**3** Click on Analysis ToolPak and click 'Go'

**4** Tick the Analysis ToolPak and press 'OK'

**5** If installed correctly, a data analysis button will exist in the Data tab of the ribbon

Statistics is simply the process of collecting, analyzing and interpreting data.

Statistics help you gain valuable insights into your business that can dramatically improve performance.

For many people who have not studied the topic, the word statistics can elicit fears of complicated maths, and strange terms such as chi squared and confidence intervals.

And to be honest with you, statistics can become very complicated and it does have a lot of strange terms.

But it turns out that the branch of statistics that most businesses need, called descriptive statistics, can be quite straightforward.

And the hard stuff, inferential statistics, can normally be left to statisticians, engineers and other data specialists.

Descriptive statistics, the focus of this course, can be used when we have access to all the data points we wish to analyze and draw conclusions from.

An example of this might be a company's sales transaction data.

For inferential statistics, we make predictions about a population based on a small sample of data taken from that population.

We typically use samples if it’s too time consuming or expensive to analyze the whole population.

A classic example of inferential statistics is a political poll where we have a total population that's too costly to analyze.

So instead, we take a random sample, of say 1.000 people.

This sample would then be asked how they would vote in the next election, and then a national poll is inferred from this sample.

This process of inferring is where much of the complication in statistics arises.

If you’re interested in learning more about inferential statistics, I will have a future course on the topic.

But in this course, we’ll be focusing totally on descriptive statistics.

Over the course of the next dozen or so lessons, we'll use Excel to perform statistical analysis on a company called Virtuoso Sports Bar, and their daily revenues from the months April to June.

Excel has many inbuilt functions to help us with statistical analysis, most of which can be found in the Formulas tab of the ribbon under More Functions and Statistical.

Most of these complicated commands, such as Chi Squared and Gamma Distributions, are related to inferential statistics, and we won't be using them in this course.

Others however, such as Standard Deviation, we will be using.

In addition to this list, Excel has an add-in called Analysis ToolPak, which has some useful statistical tools.

Analysis ToolPak is not automatically installed in Excel, and I'll now show you how to install it.

First click on the File tab in the ribbon and go to Options.

I'll then go to Add-Ins and select the Analysis ToolPak.

I'll then press Go, tick the ToolPak and press OK.

And if the ToolPak has been loaded correctly, you'll find this Data Analysis command on the right hand side of the Data tab in the ribbon.

If you're using an earlier version of Excel, the installation process for the add-in might be slightly different, and you may need your installation disk to install it.

Once we have the ToolPak installed correctly, we can now start analyzing our data in the next lesson.

# Contents

#### 1. Introducing Statistics

3 mins

#### 2. Average, Median and Mode

4 mins

#### 3. Interpreting Percentiles

4 mins

#### 4. Creating Databins

3 mins

#### 6. Finding Trends in Data

4 mins

#### 7. Correlation

5 mins