9 – Variance & Standard Deviation Final Points

A few quick final points to keep in mind about the standard deviation. First, the standard deviation is frequently used to compare the spread of different groups to determine which is more spread out. Second, when data pertains to money or the economy, having higher standard deviation is associated with having higher risk. In comparing … Read more

8 – Why the Standard Deviation_

So it might seem absurd to do this calculation of the standard deviation. I mean, it’s such a complicated way to measure the spread of our data compared to the five number summary we saw earlier. But it turns out that the standard deviation is used all the time to get a single number to … Read more

7 – Standard Deviation Calculation

In the last video, we got an idea of what the standard deviation is measuring. In this video, we will look at the math that actually occurs when calculating this measure. We will work with data to calculate this measure as well as associate notation with it. It is worth noting that after this lesson, … Read more

6 – What is the Standard Deviation Measuring_

The most common way that professionals measure the spread of a data set with a single value is with the standard deviation or variance. Here, we will focus on the standard deviation, but we will actually learn how to calculate the variance in the process. If you have never heard of these measures before, this … Read more

5 – 5 Number Summary to Variance

Looking back at the distributions we found for the number of dogs I see, we can mark the values of our five number summary like this. If we take just these marks, this makes a common plot for data known as a box plot. Though I prefer a histogram in most cases, a box plot … Read more

4 – 29 Number Summary

One of the most common ways to measure the spread of our data is by looking at the Five Number Summary, which gives us values for calculating the range and interquartile range. The Five Number Summary consists of five values, the maximum, the minimum, the first quartile, the second quartile which is also the median, … Read more

3 – What is the Difference_

Here, are two histograms comparing the number of dogs that I saw on weekdays to the number of dogs I saw on weekends from last year. You will notice that the tallest bins for both weekdays and weekends are associated with 13 dogs. So the number of dogs I expect to see are essentially the … Read more

2 – Histograms

It is easy as to understand the spread of our data visually. The most common visual for quantitative data is known as a histogram. In this video, we will take a look at exactly how histograms are constructed. In order to understand how histograms are constructed, consider we have the following data-set. First, we need … Read more

16 – Descriptive Statistics Summary

Congratulations on making it through the statistics portion of this program. This foundation in working with data will make later sections using Spreadsheets, SQL and Tableau more intuitive. I hope this section reinforce some ideas you’re already familiar with, while also introducing you to some new ones that you’ve now mastered.

15 – Descriptive vs. Inferential Statistics

The topics covered this far have all been aimed at descriptive statistics. That is, describing the data we’ve collected. There’s an entire other field of statistics known as inferential statistics that’s aimed at drawing conclusions about a population of individuals based only on a sample of individuals from that population. Imagine I want to understand … Read more

14 – Outliers Advice

If you’re the one doing the reporting, here are some of my personal guidelines when analyzing data. First, plot your data. Second, if you have outliers, determine how you should handle them. This might require a domain expert of the field. Should you remove them? Should you fix them? Should you keep them? Third, if … Read more

13 – Working with Outliers

How should we work with these outliers in practice? At the very least, we should note that they exist. We need to realize the impact they have on our summary statistics. In this case, greatly increasing our mean and our standard deviation. If the outliers are typos or data entry errors, this is a reason … Read more

12 – Outliers

In this video, we want to look at the final aspect used to describe quantitative variables, Outliers. Outliers are data points that fall very far from the rest of the values in our data set. In order to determine what is very far, there are a number of different methods. My usual method for detecting … Read more

11 – Data in the Real World

If you’re working with data, you can always build a Quick Plot to see the shape. Just to apply some context, some examples of approximately Bell-Shaped data include heights and weights, standardized test scores, precipitation amounts, the mean of a distribution, or errors in manufacturing processes. Common data that follow Left Skewed Distributions include GPAs, … Read more

10 – Shape of Distributions

Now that we’ve discussed how to build a histogram, we can use this to determine the shape associated with our data. Here we have three histograms, showing the shape for three different data sets. The histogram that has shorter bins on the left and taller bins on the right, is considered a left skewed shape. … Read more

1 – 26 Spread Part 1

That last section was intense. I hope the quizzes reinforce what was shown in the videos. I know the first time I saw a notation, it totally went over my head. We will begin this lesson looking at the second aspect with regard to analyzing quantitative variables, the spread. When we discussed measures of spread, … Read more