Flashcards in Chapter 1 Deck (52)

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1

## Cases

###
The objects described by a set of data.

Ex. Customers, companies, subjects in a study, stock

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## Label

### Is a SPECIAL VARIABLE used in some data sets to distinguish the different cases

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## Variable

### Is a characteristic of the case--> different cases can have different values for variables

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## Observation

### Describes the data for a particular case

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## Categorical Variable

###
Places a case into one of several groups or categories

Ex. Bar Graphs, Pie Charts, and Pareto Charts

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## Quantitative Variable

### Takes numerical values arithmetic operations, such as adding and averaging, makes sense

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## Statistical Software

### In some statistical software spaces are not allowed in variable names--> instead use an underscore

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## Ordered Categorical Variable

### Possible values for a grade...A, B, C, D..etc because A is better than B which is better then C and so on

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## Nominal Variable

### A categorical variable that is not ordered

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## Instruments

### Different areas of application (marketing) can also have their own special variables--> these variable are measured with instruments

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## Rate

### Computing a rate is one of several ways of adjusting one variable to create another--> sometime more meaningful than count

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## Distribution

### Describes how to values of a variable vary from case to case

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## Pareto Chart

###
Categories are ordered from MOST frequent-->least frequent-->most important categories for a categorical variable

Ex. frequently used in quality control settings

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## Histogram

### The most common graph of the distribution of a quantitative variable wear we group near values into classes--> for small data sets a stemplot can be used

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## How can you describe the overall pattern of a histogram

### You can describe the overall pattern of a histogram by its SHAPE, CENTER, and SPREAD

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## Outlier

### The most important type of deviation--> an individual value that falls outside the overall pattern

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## When is a distribution symmetric?

### If the right and left sides of the histogram are mirror images of each other

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## Skewed to the right

### If the right side of the histogram extends much farther out than the left side..and vice versa

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## Positively skewed

### Data that skews to the right--> positive skewness is the MOST common type of skewness that we see in real data

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## Time plot

### Plots each observation against the time it was measured--> time on a horizontal and the variable you are measuring on a vertical scale

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## Mean

### The most common measure of center is the ordinary arithmetic average--> NOT a resistant measure of center as it can be influenced by outliers

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## Median

### The median is the midpoint of a distribution, the number such that half the observations are smaller and half are larger

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## Median Odd

### (N+1)/2 observations up from the bottom of the list

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## Median Even

### It is the mean of the two numbers in the middle

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## Median vs Mean

### The median is more resistant than the mean

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## Median and Mean in a Symmetric Distibution

### They are close together--> exactly symmetric exactly the same

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## Median and Mean in a skewed distribution

### The mean is farther out on the long tail than the median

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## The five number summary

### Boxplot-->consits of the smallest observation, the first quartile, the median, the thrid quartile, and the largest observation --> in order form largest to smallest

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## The five number summary vs. distribution

### Not the most common numerical description of distribution

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