# Creating time series

## Video: Creating time series

In the last movie, we looked at how to create scatter plots for two quantitative variables or scale variables in SPSS. Now scatter plots are extremely useful, for exploring new data, and they're also extremely flexible. One variation on this scatter plot though deserves special mention. The time series scatter plot or time plot. As you might guess, the major difference in this case is that the variable that goes across the bottom on the x-axis is some measure of time. Another difference is that time plot often have only one measurement for each time period whereas scatter plots can have, for example, lots of people who are all at the same point on the x-axis.

## Creating time series

In the last movie, we looked at how to create scatter plots for two quantitative variables or scale variables in SPSS. Now scatter plots are extremely useful, for exploring new data, and they're also extremely flexible. One variation on this scatter plot though deserves special mention. The time series scatter plot or time plot. As you might guess, the major difference in this case is that the variable that goes across the bottom on the x-axis is some measure of time. Another difference is that time plot often have only one measurement for each time period whereas scatter plots can have, for example, lots of people who are all at the same point on the x-axis.

Because all time plots usually have only one observation at each point in time, you can also connect the points, which makes it more like a line chart. And here's how it works in SPSS. For this example, I'm going to be using the data set that's called NDAQ.sav. And what this is the price for shares in the NASDAQ Exchange itself, from 2002 through 2011. It only has two variables. It has the first market day of each month and it has the closing price on that day for each month.

Let's go up to Graphs and then to Chart Builder and then down to Scatter and choose the Simple Scatter, the top left one, and drag it into the canvas. The Date will go on the bottom and the closing price for the NASDAQ stocks will go on the left, and that's how we need to do right here. I am going just going to click OK, and what you see is a lot of dots. Now, you can see the pattern. It starts relatively low in '04 or '05, shoots way up high in '06 and 'O8, comes back down to earth in 2010, and then starts to go back up again.

But there's a way to make this chart much clearer. We just need to edit it, and do a few different things. So to edit it, like every other chart first we double click on it to open up the editing window. And for this one, what we want to do is we want to click on the button in the menu bar here. It's called Add Interpolation Line. And what this does is it draws a line that connects every dot across the bottom. This is the standard line plot, you would expect every time. Now, if we stop right there, it's not bad.

However, at this point the dots actually get in the way, and so what we can do, is we can click carefully on the dots. So they are all selected and just hit Delete, and we our left with the line plot that shows the pattern more clearly than the dots themselves, of things starting slowly, skyrocketing and then coming back down at the end of the dotcom bubble. And that is a special case where the predictor variable is time and you can adapt the standard scatter plot to show how a variable changes, in which case it's now called the Time Series Scatter Plot or Time Plot.

This is a good example of how SPSS helps you customize your charts to make them easier to read and more useful in interpretation. Up to this point, we have looked at charts for the association of two categorical variables and two scale variables. In the next few movies, we will look at the combination of the two kinds: charts that show the association of one categorical variable and one scale variable.

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#### This video is part of

SPSS Statistics Essential Training (2011)

52 video lessons · 21704 viewers

Author

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1. ### Introduction

2m 58s
1. Welcome
1m 5s
2. Using the exercise files
40s
3. Using a different version of the software
1m 13s
2. ### 1. Getting Started

19m 0s
1. Taking a first look at the interface
11m 49s
7m 11s
3. ### 2. Charts for One Variable

21m 54s
1. Creating bar charts for categorical variables
7m 18s
2. Creating pie charts for categorical variables
2m 54s
3. Creating histograms for quantitative variables
5m 45s
4. Creating box plots for quantitative variables
5m 57s
4. ### 3. Modifying Data

33m 10s
1. Recoding variables
5m 33s
2. Recoding with visual binning
5m 33s
3. Recoding by ranking cases
5m 26s
4. Computing new variables
5m 37s
5. Combining or excluding outliers
5m 21s
6. Transforming outliers
5m 40s
5. ### 4. Working with the Data File

28m 12s
1. Selecting cases
6m 44s
2. Using the Split File command
5m 12s
3. Merging files
5m 33s
4. Using the Multiple Response command
10m 43s
6. ### 5. Descriptive Statistics for One Variable

22m 14s
1. Calculating frequencies
8m 43s
2. Calculating descriptives
5m 31s
3. Using the Explore command
8m 0s
7. ### 6. Inferential Statistics for One Variable

16m 3s
1. Calculating inferential statistics for a single proportion
6m 6s
2. Calculating inferential statistics for a single mean
5m 39s
3. Calculating inferential statistics for a single categorical variable
4m 18s
8. ### 7. Charts for Two Variables

30m 43s
1. Creating clustered bar charts
7m 10s
2. Creating scatterplots
5m 8s
3. Creating time series
3m 24s
4. Creating simple bar charts of group means
4m 17s
5. Creating population pyramids
3m 0s
6. Creating simple boxplots for groups
3m 3s
7. Creating side-by-side boxplots
4m 41s
9. ### 8. Descriptive and Inferential Statistics for Two Variables

45m 28s
1. Calculating correlations
8m 17s
2. Computing a bivariate regression
6m 27s
3. Creating crosstabs for categorical variables
6m 34s
4. Comparing means with the Means procedure
6m 33s
5. Comparing means with the t-test
6m 4s
6. Comparing means with a one-way ANOVA
6m 30s
7. Comparing paired means
5m 3s
10. ### 9. Charts for Three or More Variables

24m 30s
1. Creating clustered bar charts for frequencies
6m 34s
2. Creating clustered bar charts for means
3m 45s
3. Creating scatterplots by group
4m 13s
4. Creating 3-D scatterplots
4m 25s
5. Creating scatterplot matrices
5m 33s
11. ### 10. Descriptive Statistics for Three or More Variables

30m 57s
1. Using Automatic Linear Models
11m 52s
2. Calculating multiple regression
9m 3s
3. Comparing means with a two-factor ANOVA
10m 2s
12. ### 11. Formatting and Exporting Tables and Charts

29m 29s
1. Formatting descriptive statistics
6m 1s
2. Formatting correlations
7m 49s
3. Formatting regression
10m 19s
4. Exporting charts and tables
5m 20s
13. ### Conclusion

51s
1. What's next
51s

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