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Summary Statistics for Business and Economics

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Summary chapter 1 - 15 18 Statistics for Business and Economics, Third edition Jim Freeman & Eddie Shoesmith 9781408072233

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Statistics for Business and Economics

Chapter 1 Data and Statistics
Qualitative variables
Into which of several categories a population unit falls.

Nominative variables
- Categories  there is no meaningful ordening or ranking.
For example: gender, color of a car.

Ordinal variables
- Values can be meaningfully ranked.
For example: ordered from low to high, more or less, small to large.


Quantitative variables
Numbers that represent quantities.

Interval variables
- There is not an inherently defined zero point. The value can be negative. De schaal loopt in
theorie van min oneindig naar plus oneindig.
For example: temperature.
- Can only meaningfully compare values by the interval between them:
Cannot compare values by taking their ratios.
“Interval” is the arithmetic difference between the values.

Ratio variables
- There is an inherently defined zero point. The value cannot be negative. De variabelen lopen
van 0 tot plus oneindig.
For example: weight of a subject (cannot be less than zero).
- Values can be compared in terms of their interval and ratio.

, Chapter 2 Descriptive Statistics: Tabular and Graphical Methods
2.1 Graphically Summarizing Qualitative Data

Frequency distribution  a table that summarizes the number (or frequency) of items in each of
several nonoverlapping classes.

Frequency  hoe vaak een item van een bepaalde groep voorkomt.

Relative frequency  frequency of the class / n  n = the total number of observations.
Gegeven in komma-getallen, alle relative frequencies bij elkaar opgeteld is 1.0.
Weergegeven in een Relative frequency distribution.

Percent frequency  multiplying the relative frequency by 100%.
Weergegeven in een Percent frequency distribution.

Bar chart (staafdiagram)  a graphic that depicts a frequency, relative frequency or percent
frequency distribution.
- Horizontal axis  label for each class.
- Vertical axis  frequencies (can also be relative or percent frequencies).
The bars have gaps between them  when data are qualitative, the bars should always be separated
by gaps in order to indicate that each class is separate from the others.
Vertical and horizontal bar charts are both possible.

Pie chart (cirkeldiagram)  another graphic that can be used to depict a frequency distribution.
The circle represents the entire data set.

The Pareto Chart  to help identify important quality problems and opportunities for process
improvement. See figure 2.4, p.38.
- It is a bar chart having the different categories list on the horizontal scale.
- The heights of the bars on the vertical scale represent the frequency or the percentage of
occurrence for each category.
- The bars are arranged in decreasing height from left to right.
- If an “other” category is employed, its bar is placed at the far right.
- A Pareto chart is sometimes augmented by plotting a cumulative percentage points for each
bar.

2.2 Graphically Summarizing Quantitative Data

Histogram  a graphical display of a frequency distribution (staafdiagram), relative or percentage
frequency distribution. It divides measurements into into classes and graphs the frequency for each
class. 5 steps:

1. Find the number of classes  2K rule
K = number of classes
2K has to be greater than the number of measurements.
For example: 65 measurements, how many classes?
If K=6  26 =64
If K=7  27 =128
128 > 65, so the number of classes has to be 7.

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