Descriptive statistics on SPSS is just like mandatory knowledge that everyone should have. It is the basic thing that works almost in every statistical analysis.

If you are working in huge numbers of data, descriptive statistics help you to provide the summary and the characteristics of the data.

There is a lot of software you may use to do the analysis. But in SPSS, you may do it in the easiest and fastest way. Also, it shows you sequentially so it really helps to make a report.

Descriptive statistics is a statistical analysis process that focuses on management, presentation, and classification which aims to describe the condition of the data.

With this process, the data presented will be more attractive, easier to understand, and able to provide more meaning to data users.

In general, descriptive statistics must be able to give an idea of what information can be obtained from the data we use. Instead of just using numbers without a standard format, it would be more interesting if displayed in graphs and tables.

Descriptive statistics also provide characteristics of the data used. This is important because the condition of the data used will affect the entire data analysis that we do.

By using SPSS, you may get these two goals easily.

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## Why using SPSS to run Descriptive Statistics?

As a researcher, there are a lot of software which we can use to generate descriptive statistics. Each software has their own benefit.

Allow me to explain why you should use SPSS to do your descriptive statistics job!

1. Simple and Easy to use

SPSS is software that is easy to use by all community. The available features have been designed so it can be used even by beginners who don’t really have statistics or coding basic.

2. Complete numerical analysis

You may see the complete numerical analysis in descriptive statistics if you run the data with SPSS.

You have measure of central tendency which consist of mean, median, modus as the most popular and mandatory analysis.

Also, you could easily generate measure of dispersion such as variance, standard error, standard deviation, range, skewness, and kurtosis to help you see how the data spread.

Quartile, percentile, minimum, and maximum are also available as measure of position.

Still, you could also produce the histogram, steam and leaf diagram, z-score etc to give you detail explanation about the data condition.

3. Full customization

What matter is, you have full control of the descriptive statistics summarize. You may choose what do you want to show and which one you do not need. All is easy by simple click.

Also, you may do your own code in case you want to try to customize the descriptive statistics output. SPSS also provide this option for you

**Steps of Descriptive Statistics on SPSS**

There are 3 options that you can use in SPSS to do descriptive statistics. Every option has its own statistics that you want to show. Also, some statistics can be found in other options.

Do not worry, let me explain it clearly one by one for you!

**Using Frequencies Menu in descriptive analysis**

1. Choose **Analyze > Descriptive Statistics >> Frequencies**

2. Move the variables that we want to analyze. In this example, let’s use **gender, height**, and** weight**.

3. On the right side of the submenu, you will see three options you could add; statistics, chart, and format. This is what you will get if you click **statistics.**

4. You can do another descriptive analysis on this menu. But, in this case, I prefer to use default options so we could see the difference between the. So let’s ignore the additional menu, okay!

5. Click **Ok**

6. This is the result of the output window

**Interpretation of Descriptive Statistics Frequencies Output**

1. In the first chart, it shows the numbers of valid data and missing data. From the table, we could conclude that there are 13 valid data for gender, 12 for height, and 12 for weight. There is one missing for each height and weight variable.

This table could help you to analyze whether your data is complete or not.

2. In the gender frequency table, we could see the percentage analysis of the groupset. You could see, 53.8 percent of the sample is female and 46.2 percent of the sample is male. It means, we use more females than males in this research.

3. In the height frequency table, you will see the frequency analysis of height. At the frequency column, you’ll see 1 for every height value. It means, we have one person that has the height in the groupset. At the bottom, you’ll also see the total and missing value of the group.

4. In the weight frequency table, you will see the frequency analysis of weight. At the frequency column, There is 2 value in 70kg row. It means there are two people who have the same weight in the groupset.

1. Choose **analyze >> descriptive statistics >> descriptive**

2. Set the variable you want to analyze. In descriptive, we could only analyze the ordinal and scale variables

3. Check at the menu tab if you want to put another option. In this term, I would like to use the default condition.

4. Check the box of standardized value options.

5. Click Ok.

Interpretation of the SPSS output:

1. You’ll see there is 12 valid value of height and weight, no summarize of missing value here.

2. The minimum value of height is 160 cm, the maximum value is 175. The mean value is 168.08 cm.

3. For weight, the minimum value is 60 kg and the maximum value is 79 kg. The mean value 68.67 kg.

4. The standard deviation for height 4.680. It means, the data relatively distributed near the mean value.

5. The standard deviation for weight is 6.344. It means, the data relatively distributed near the mean value.

6. When you look at the data view, you’ll see two additional variables. This is the standardized value or z-score which we activated before. The smaller the number, the closer to the average. The greater the number, the further it is from the average. A positive sign indicates that the value is above average while negative means below average.

**Explore descriptive analysis on SPSS**

1. Choose **analyze >> descriptive >> explore**

2. Set the variable we want to analyze. Here, I put height and weight to the dependent list and gender to the factor list.

3. We have three additional menu; statistics, plot, and chart. Here, my favorite is the plot because I could see the histogram. Let me check it by choosing **a plot >> histogram**. You can always add your own favorite.

4. Continue >> Ok

5. See the output window

**Interpretation of exploring the menu on descriptive statistics**

1. In the case processing summary, you will see the complete frequency analysis of the group set, the valid and the missing cases.

2. In the descriptive table, you also see the complete descriptive table for height and weight by gender. You’ll see the central tendency to measures of dispersion. You also see the confidence interval of the mean.

3. SPSS also provides each histogram for the dependent list. If you are using any data, you’ll see the pattern of distribution.

4. Steam and leaf plots makes it easier to read the data.

5. Also, we have a boxplot to see how the data distributed from the mean value.

**Disadvantages of using SPSS to Run Your Descriptive Statistics**

Although SPSS is a phenomenal software that helps a lot in the world of research, here are the weaknesses I found in its use.

1. The chart feature is bad

In the beginning, I already told you that descriptive statistics purpose is also providing data visualization. It helps us as the researcher or also the reader to make the data easier to understand.

But, SPSS could not provide the chart customization beautifully. The chart output is plain, flat, and far from reasearch or publication standard.

Honestly, I prefer to use Microsoft Excel to produce an interesting and informative chart.

2. It is expensive

Yes, the price of the license to use SPSS legally is expensive. Not all people or communities could afford it. Check this page!

I think the price is out of common people reach which use the software for only basic statistical process.

If you just only want to create a simple and basic formula, you may do it by using descriptive statistics with excel. It is quite easy and super simple.

**How to write a descriptive analysis report**

Now, how to write the descriptive analysis report properly? How to explain it to the reader so they will understand it and have a meaningful insight.

Usually, I categorize my report like this.

1. Specify the measure of central tendency.

Mean, median, and modus are the top three that always we have to put in the report. You may write it for each variable so you will see the difference between them.

2. Specify the measure of dispersion

Variance and standard deviation are the most important part that you have to put on the report.

3. Analyze the value of data

The value that you have to put is minimum, maximum, range, and outlier. We could detect that your data is normally distributed or not by using this.

4. Analyze the shape distribution

Use kurtosis and skewness to measure the shape of data distribution. It helps to decide how the data distributed from the mean. Also, show the histogram!

5. Make a proper explanation

After deciding the numbers above, make a correct explanation, and check the relationship with the fact.

**Conclusion**

SPSS Descriptive Statistics is powerful. This three menu is the common thing that researcher to analyze the data. Let me summarize it.

1. There is three submenus in descriptive statistics we can use; frequencies, descriptive, explore

2. Use frequencies to show the frequency analysis

3. Use descriptive statistics to show the basic analysis

4. Use explore to make an advanced and detail analysis

5. Read the output carefully and make the report amazingly!

This is my best explanation of using SPSS for descriptive statistics. Are you having some trouble in implementing or interpreting the output? Let’s learn descriptive statistics from the scratch to.

Leave your comment below and let’s have a discussion.

I would love it.