About This Chapter
Statistics: Principles and Techniques - Chapter Summary
This chapter will take you through the most essential information you need to know about principles and techniques and statistics. You will be able to refresh your knowledge on elements such as: measures of central tendency, visual representation of a data set, frequency tables, pie charts and histograms. After completion of the lessons in this chapter you should have the knowledge to:
- Create stem and leaf displays
- Use dot plots and box plots
- Explain spread in data sets
- Determine standard deviation
- Compare populations and samples used in statistics
- Define random sampling
- Understand bias
Using this chapter to review principles and techniques of statistics can be a time-saving and engaging endeavor. The video lessons can be viewed on a variety of devices, which can help you customize your study for convenience and flexibility. Quizzes throughout the chapter will allow you to quickly assess your knowledge and help determine the areas which may need further review. Subject-matter experts are available should you need further clarification on any of the material.
1. Frequency & Relative Frequency Tables: Definition & Examples
Frequency and relative frequency tables are a good way to visualize information. This is especially useful for information that is grouped into categories where you are looking for popularity or mode.
2. Creating & Reading Stem & Leaf Displays
Every once in a while you will come across stem-and-leaf displays in statistics. These displays can be very useful in identifying all of the values in a data set while still visually representing the data.
3. Creating & Interpreting Histograms: Process & Examples
Creating histograms can help you easily identify and interpret data. This lesson will give you several examples to better understand histograms and how to create them.
4. Creating & Interpreting Dot Plots: Process & Examples
Dot plots are a visual way to display the frequency distribution in a data set. In this lesson, you will learn how to construct a dot plot and understand its uses.
5. Creating & Interpreting Box Plots: Process & Examples
Box plots are an essential tool in statistical analysis. This lesson will help you create a box plot and understand its meaning. When you are finished, test your understanding with a short quiz!
6. Understanding Bar Graphs and Pie Charts
In this lesson, we will examine two of the most widely used types of graphs: bar graphs and pie charts. These two graphs can provide the reader with a comparison of the different data that is displayed.
7. What is the Center in a Data Set? - Definition & Options
Finding the center in a data set can sometimes be a little confusing. This lesson will help you determine the correct method for finding the center in a data set, and when you are finished, test your knowledge with a short quiz!
8. Mean, Median & Mode: Measures of Central Tendency
By describing the data using central tendency, a researcher and reader can understand what the typical score looks like. In this lesson, we will explore in more detail these measures of central tendency and how they relate to samples and populations.
9. How to Calculate Mean, Median, Mode & Range
Measures of central tendency can provide valuable information about a set of data. In this lesson, explore how to calculate the mean, median, mode and range of any given data set.
10. Visual Representations of a Data Set: Shape, Symmetry & Skewness
Visual representations are a fantastic way of understanding and analyzing your data. Use this lesson to understand the characteristics of visual representations of data.
11. Spread in Data Sets: Definition & Example
Identifying the spread in data sets is a very important part of statistics. You can do this several ways, but the most common methods are through range, interquartile range, and variance.
12. Calculating the Standard Deviation
In this lesson, we will examine the meaning and process of calculating the standard deviation of a data set. Standard deviation can help to determine if the data set is a normal distribution.
13. Difference between Populations & Samples in Statistics
Before you start collecting any information, it is important to understand the differences between population and samples. This lesson will show you how!
14. What is Random Sampling? - Definition, Conditions & Measures
Random sampling is used in many research scenarios. In this lesson, you will learn how to use random sampling and find out the benefits and risks of using random samples.
15. Bias in Statistics: Definition & Examples
Statistics can be a powerful tool in research. Unfortunately, statistics can also have faults. In this lesson, you will learn about the faults in statistics and how to critically examine potential biases in research.
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