Back to 课程

Statistics Gcse Edexcel Higher

0% Complete
0/0 Steps
  1. Planning-And-Types-Of-Data gcse Edexcel Higher
    2 主题
  2. Population-Sampling-And-Collecting-Data gcse Edexcel Higher
    2 主题
  3. Tabulation-Diagrams-And-Representation gcse Edexcel Higher
    10 主题
  4. Measures-Of-Central-Tendency gcse Edexcel Higher
    5 主题
  5. Measures-Of-Dispersion gcse Edexcel Higher
    4 主题
  6. Using-Summary-Statistics gcse Edexcel Higher
    3 主题
  7. Index-Numbers-And-Rates-Of-Change gcse Edexcel Higher
    2 主题
  8. Scatter-Diagrams-And-Correlation gcse Edexcel Higher
    4 主题
  9. Time-Series gcse Edexcel Higher
    3 主题
  10. Quality-Assurance-And-Estimation gcse Edexcel Higher
    2 主题
  11. Probability-Basics gcse Edexcel Higher
    4 主题
  12. Probability-Distributions gcse Edexcel Higher
    2 主题
课 Progress
0% Complete

Exam code:1ST0

Characteristics of the Normal Distribution

What is a normal distribution?

  • A normal distribution is a probability distribution that can be used with continuous quantities

    • The distribution is symmetrical and bell-shaped about the mean

    • The mean, median, and mode are all equal

  • The notation for a normal distribution is straight N open parentheses mu comma space sigma squared close parentheses

    • mu is the mean of the distribution

    • sigma squared is called the variance of the distribution

      • it is a measure of how spread out the data is

      • it is equal to the standard deviation (sigma) squared

  • If the mean changes but the standard deviation (or variance) stays the same

    • then the shape of the distribution stays the same

  • If the standard deviation (or variance) increases but the mean stays the same then the distribution is stretched out horizontally

    • A small standard deviation (small variance) means a tall curve with a narrow centre

    • A large standard deviation (large variance) leads to a short curve with a wide centre

4-3-1-the-normal-distribution-diagram-1

When is a normal distribution a suitable model for a distribution of data?

  • To use a normal distribution to model a distribution of data, the following must be true

    • The data must be continuous

      • e.g. height or weight (in the real world, heights and weights of populations are often normally distributed)

    • The distribution must be symmetrical and bell-shaped

      • Most data points near the middle

      • Decreasing evenly to right and left

    • The mean, median and mode must be approximately equal

      • They don’t need to be exactly equal, but should be close

      • This means that a normal distribution is not appropriate for skewed data

How are the data points distributed in a normal distribution?

  • For a normal distribution straight N open parentheses mu comma space sigma squared close parentheses

    • The mean (and mode and median) is μ

    • The standard deviation is <img alt=”sigma” data-mathml=”<math ><semantics><mi>&#963;</mi><annotation encoding=”application/vnd.wiris.mtweb-params+json”>{“fontFamily”:”Times New Roman”,”fontSize”:”18″,”autoformat”:true,”toolbar”:”<toolbar ref=’general’><tab ref=’general’><removeItem ref=’setColor’/><removeItem ref=’bold’/><removeItem ref=’italic’/><removeItem ref=’autoItalic’/><removeItem ref=’setUnicode’/><removeItem ref=’mtext’ /><removeItem ref=’rtl’/><removeItem ref=’forceLigature’/><removeItem ref=’setFontFamily’ /><removeItem ref=’setFontSize’/></tab></toolbar>”}</annotation></semantics></math>” height=”22″ role=”math” src=”data:image/svg+xml;charset=utf8,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20xmlns%3Awrs%3D%22http%3A%2F%2Fwww.wiris.com%2Fxml%2Fmathml-extension%22%20height%3D%2222%22%20width%3D%2212%22%20wrs%3Abaseline%3D%2216%22%3E%3C!–M

Responses

您的邮箱地址不会被公开。 必填项已用 * 标注