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Statistics - summary

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  • Course
  • Statistics Stenden Year 2 - Design Module
  • Institution
  • NHL Stenden Hogeschool (NHL)

A summary of all the statistics lectures and workshops given in the second year of the education IHM at Stenden University of Applied Sciences. Not only the lectures, but also other relevant information is provided in this summary. The relevant information comes from the book Statistics written by ...

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Document information

  • May 30, 2017
  • June 9, 2017
  • 9
  • 2016/2017
  • Exam (elaborations)
  • Only questions

Subjects

  • statistics
  • design
  • stenden
  • ihm
  • senior hotelchool
  • year 2
  • test
  • exam
  • exam
  • examples
  • questions
  • summary
  • summary

Written for

  • NHL Stenden Hogeschool (NHL)
  • Hoger Hotelmanagement
  • Statistics Stenden Year 2 - Design Module
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Content preview

Statistics
Lecture 1: The Normal Distribution
Descriptive Statistics
Mean (μ) = describes the central point of a distribution
Standard Deviation (σ) = describes the variation of a distribution. Small amount if it is close to the
average. The higher amount, the more variation.

These two numbers describe / summarize a group of data.

Descriptive Measures
x =∑x/n = calculating the average outcome

 Average
X  Outcome
N  Number of outcomes
∑  Sum

S = √ ∑ ( x – x ) ^2 / n – 1 = calculating the standard deviation
Probability
How many people do actually have a certain score? Chance that a certain event occurs.

Probability Distribution = list of all possible events, with their probability

The Normal Distribution

Symmetrical, bell-shaped curve. Horizontal are all
scores and vertical are the frequency. In the
middle, you can find the average. The whole
normal distribution is 100%. The smaller the
standard deviation, the sharper the shape of the
bell.

Most people are average, some people are special
and a few people are extreme.



The Standard Normal Distribution
- Probabilities in the standard normal distribution can be found in a table
- N (0,1): mean = 0 and standard deviation is 1.

The Standard Score
- Describes the distance from the mean, in number of standard deviations
- Z = (X – μ) / σ
- The score is now standardized, thus the probability distribution of Z is a standard
normal distribution
- ALL normal distributions can be transformed into the STANDARD normal distribution

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