STA 2023 unit 1 vocab

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statistics

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the study of how to collect/organize/analyze/interpret numerical information from a data set

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individuals

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people/object included in the study (2 types)

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Statistics

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32 Terms

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statistics

the study of how to collect/organize/analyze/interpret numerical information from a data set

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individuals

people/object included in the study (2 types)

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variables

characteristics of the individuals to be measured or observed (2 types)

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population data (parameter)

the data from each individual in the population of interest

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sample data (statistic)

comes from some individuals in the population of interest

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nominal level

applies to data that consists of names/labels/categories, order doesn't matter

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ordinal level

applies to data that can be arranged in order, not numerical

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interval level

numerical measurements with no true zero or the ratio isn't meaningful

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true zero

if the measurement is converted into other units then the result would be zero

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ratio level

data with meaningful ratios, have a true zero

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simple random sampling

selected randomly with a number table or computer, each individual/sample of the population has equal chances of being selected

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stratified sampling

population divided into several groups and then a simple random sample is drawn from each group

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systematic sampling

elements of the population are arranged in order and then every kth element is selected with a random starting point

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cluster sampling

population are is divided into sections and then some sections are randomly selected with every individual of each section included in the sample

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convenience sampling

has a time/location limit and not every individual of the population has a chance of being selected

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multistage sampling

using a combination of sampling methods to create smaller groups at each stage (not convenience, last stage is cluster)

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class requirements

every data value must fall into one of the classes
the classes must not overlap
the classes must be of equal width
there must be no gaps between classes

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relative frequency

class frequency/total number of data values

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relative frequency percentage

relative frequency * 100

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cumulative frequency

sum of the frequencies for that class and previous classes

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mount shaped symmetric

T shaped, mean/median/mode are equal

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skewed to the left

rises to the right, mean<median<mode

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skewed to the right

rises to the right, mode<median<mean

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unimodal

only has 1 peak/mode

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bimodal

has 2 peaks/modes

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population mean

u, sum of xi over N (N is the population size)

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sample mean

x_, sum of xi, over n (n is the sample size)

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deviation

xi-mean (u or x_), negative=value below average, positive=value above average

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coefficient of variation

(standard deviation/mean) * 100, small=most of the data is split around the mean, large=data values are split everywhere

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outlier

a value that's considerably small or large

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lower outlier limit

Q1-1.5(LQR)

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upper outlier limit

Q3+1.5(LQR)