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### Using Linear Regression to Predict an Outcome

Statistical researchers often use a linear relationship to predict the (average) numerical value of *Y* for a given value of *X* using a straight line (called the [more…]

### How to Calculate a Regression Line

In statistics, you can calculate a regression line for two variables if their scatterplot shows a linear pattern and the correlation between the variables is very strong [more…]

### How to Interpret a Regression Line

In statistics, once you have calculated the slope and *y-*intercept to form the best-fitting regression line in a scatterplot, you can then interpret their values. [more…]

### How to Calculate a Confidence Interval for a Population Mean When You Know Its Standard Deviation

If you know the standard deviation for a population, then you can calculate a confidence interval (CI) for the mean, or average, of that population. When a statistical characteristic that’s being measured [more…]

### How to Compare Two Population Proportions

For statistical purposes, you can compare two populations or groups when the variable is categorical (for example, smoker/nonsmoker, Democrat/Republican, support/oppose an opinion, and so on) and you’re [more…]

### Working with Statistical Two-Way Tables

To explore the links between two categorical variables, you first need to organize the data that’s been collected, and a table is a great way to do that. A [more…]

### Why the Statistical Mean and Median of a Histogram Often Have Different Centers

A histogram gives you a rough idea of where the "center" of the data lies. The word *center* is in quotes because many different statistics are used to designate the center. The two most common measures [more…]

### How to Find the Interquartile Range for a Statistical Sample

To obtain a measure of variation based on the five-number summary of a statistical sample, you can find what's called the *interquartile range**,* or *IQR*.

The purpose of the five-number summary is to give descriptive [more…]

### How a Pie Chart Reflects Categorical Data in a Statistical Data Set

A pie chart takes categorical data from a statistical sample and breaks them down by group, showing the percentage of individuals that fall into each group. Because a pie chart takes on the shape of a [more…]

### How to Interpret a Statistical Bar Graph

A *bar graph* (or *bar chart*) is perhaps the most common statistical data display used by the media. A bar graph breaks categorical data down by group, and represents these amounts by using bars of different [more…]

### How Graphs Can Distort Statistics

A statistical graph can give you a false picture of the statistics on which it is based. For example, it can be misleading through its choice of scale on the frequency/relative frequency axis [more…]

### How Histograms Show Statistical Data

A *histogram* is a special graph applied to statistical data broken down into numerically ordered groups; for example, age groups such as 10–20, 21–30, 31–40, and so on. A histogram provides a snapshot of [more…]

### How to Group Statistical Data Appropriately in a Histogram

When you create a histogram, it's important to group the data sets into ranges that let you see meaningful patterns in your statistical data. For example, say you want to see if actresses who have won [more…]

### How to Place Borderline Statistical Values in a Histogram

When you create a histogram, you need to divide the data set into separate groups. However, some statistical data may be right on the borderline between two groups. What do you do in these situations? [more…]

### How to Clearly Label the Axes on a Statistical Histogram

The most complex part of interpreting a statistical histogram is to get a handle on what you want to show on the *x* and *y* axes. Having good descriptive labels on the axes will help. Most statistical software [more…]

### How Histograms Can Misrepresent Statistical Data

There are no hard and fast rules for how to create a histogram based on a set of statistical data; the person making the graph gets to choose the groupings on the [more…]

### Why You Need to Identify a Population for Statistical Research

For virtually any statistical study of a population, you have to center your attention on a particular group of individuals (for example, a group of people, cities, animals, rock specimens, exam scores [more…]

### Avoid Bias with Random Statistical Samples

How do you select a statistical sample in a way that avoids bias? The key word is *random.* A *random sample* is a sample selected by equal opportunity; that is, every possible sample of the same size as yours [more…]

### How to Identify Statistical Bias

*Bias* is a word you hear all the time in statistics, and you probably know that it means something bad. But what really constitutes bias? *Bias* is systematic favoritism that is present in the data collection [more…]

### Why Mean and Median Are Both Important in Statistical Data

In statistics, the average and the median are two different representations of the center of a data set and can often give two very different stories about the data, especially when the data set contains [more…]

### What the Distribution Tells You about a Statistical Data Set

The *distribution* of a statistical data set (or a population) is a listing or function showing all the possible values (or intervals) of the data and how often they occur. When a distribution of categorical [more…]

### Comparing Statistical Surveys and Statistical Experiments

There are two major types of statistical studies: surveys and experiments. After a question has been formed, researchers must design an effective study to collect data that will help answer that question [more…]

### Identifying Bad Statistical Samples

After a statistical study has been designed, be it a survey or an experiment, you need to select a sample of individuals who represent a cross-section of the entire population. This is critical to producing [more…]

### Identifying Statistical Bias in Your Data Sample

*Statistical b**ias* is the systematic favoritism of certain individuals or certain responses in a study. Bias is the nemesis of statisticians, and they do everything they can to avoid it. Want an example [more…]

### Describing Your Statistical Data with Numbers

After collecting good statistical data, you can summarize it with *d**escriptive statistics**.* These are numbers that describe a data set in terms of its important features: [more…]