About This Chapter
ILTS Mathematics: Collecting & Representing Data - Chapter Summary
To create statistical data successfully, you need to possess a clear understanding of data collection methodologies and representation standards. These video lessons can improve your comprehension of the process of collecting and representing data, and the more you know the better prepared you will be for related questions on the ILTS Mathematics Test. After going through the lessons in this chapter, you should know more about the following:
- The measures and conditions for random sampling
- The different types of survey research and gathering methods
- Examples of biased samples
- Vital data measurements: mode, median, and mean
- Variability measurements: standard deviation, range, and variance
- Bar graphs, leaf and stem displays, and histograms
- Scatterplots, box plots, pictographs, and line graphs
- Types of frequency distributions
- Equations that determine the line of best fit
- Statistical transformations: logarithmic and power
Probability and statistics is one of the main five sections addressed on the ILTS Mathematics Test, so to increase your chances of doing well on this section, begin at this chapter's first lesson that discusses gathering random samples and recognizing the advantages and disadvantages of randomization. The video lessons are incredibly short, so binge-watching is a doable option. If you literally only have small breaks throughout your day, you can still get through a few lessons in one sitting. Plus, we don't restrict where you can study. As long as you have a device that can get online, all of our study materials are only a click away.
1. 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.
2. What Is Survey Research? - Definition, Methods & Types
This lesson explores the ways a researcher may employ the types of surveys used in research. We will also go over the strengths and weaknesses of each type of survey.
3. What is a Biased Sample? - Definition & Examples
One goal of research is to obtain the best estimate for a population. The best estimate is an unbiased statistic representative of the population of interest. In this lesson, learn what biased samples are and how to avoid them in your research.
4. 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.
5. Measures of Variability: Range, Variance & Standard Deviation
Looking specifically at range, variance, and standard deviation, this lesson explores the relationship between these measures and samples, populations, and what it says about your data.
6. Bar Graph: Definition, Types & Examples
A bar graph is a mathematical representation of data. In this lesson, you will learn the definition of a bar graph, including how to recognize the different types of bar graphs. You will also learn how to create bar graphs.
7. 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.
8. 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.
9. 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!
10. Scatterplots and Line Graphs: Definitions and Uses
After watching this video, you will be able to understand scatter plots and line graphs. You will also be able to use them to tell people a story about what you see and observe. You will also be able to read them.
11. Frequency Distributions: Definition & Types
This lesson explores the process of creating frequency distributions and histograms to give readers of your future scientific articles a numerical or visual way to understand the data you have presented.
12. Reading & Interpreting Pictographs
Imagine reading chart after chart of the same dry information. Now imagine if that information could be presented with images and in only one chart. Much better, right? That's exactly what pictographs allow us to do.
13. Line of Best Fit: Definition, Equation & Examples
Linear graphs are a terrific way to see a trend when comparing any two factors. A line of best fit is the trendline that best fits the data set. In this lesson, we will see how the line of best fit helps to predict future events.
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Other chapters within the ILTS Mathematics (208): Test Practice and Study Guide course
- ILTS Mathematics: Concepts & Skills
- ILTS Mathematics: Logic & Reasoning
- ILTS Mathematics: Using Technology for Math
- ILTS Mathematics: Number Theory
- ILTS Mathematics: Solving Number Problems
- ILTS Mathematics: Real & Complex Numbers
- ILTS Mathematics: Measurement
- ILTS Mathematics: Multidimensional Objects
- ILTS Mathematics: Variables & Patterns
- ILTS Mathematics: Linear Relations & Functions
- ILTS Mathematics: Quadratic Relations & Functions
- ILTS Mathematics: Absolute Value
- ILTS Mathematics: Polynomials
- ILTS Mathematics: Radical Functions
- ILTS Mathematics: Rational Functions
- ILTS Mathematics: Exponential Functions
- ILTS Mathematics: Logarithmic Functions
- ILTS Mathematics: Trigonometric Functions
- ILTS Mathematics: Calculus
- ILTS Mathematics: Points, Lines, Planes & Space
- ILTS Mathematics: 2D & 3D Shapes
- ILTS Mathematics: Spatial Visualization
- ILTS Mathematics: Congruence, Similarity & Symmetry
- ILTS Mathematics: Probability Theory & Techniques
- ILTS Mathematics: Using Data to Make Predictions
- ILTS Mathematics Flashcards