Chapter 16: Running Descriptive Statistics in Access


Determining rank, mode, and median

Pulling a random sampling from your dataset

Calculating percentile ranking

Determining the quartile standing of a record

Creating a frequency distribution

Descriptive statistics allow you to present large amounts of data in quantitative summaries that are simple to understand. When you sum data, count data, and average data, you're producing descriptive statistics. It's important to note that descriptive statistics are used only to profile a dataset and enable comparisons that can be used in other analyses. This is different from inferential statistics, in which you infer conclusions that extend beyond the scope of the data. To help solidify the difference between descriptive and inferential statistics, consider a customer survey. Descriptive statistics summarize the survey results for all customers and describe the data in understandable metrics, while inferential statistics infer conclusions such as customer loyalty based on the observed differences between groups of customers.

When it comes to inferential statistics, tools like Excel are better suited to handle these types of analyses than Access. Why? First, Excel comes with a plethora of built-in functions and tools that make it easy to perform inferential statistics — tools that Access simply does not have. Second, inferential statistics is usually performed on small subsets of data that can flexibly be analyzed and presented ...

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