APST 207- Final Exam Guide - Comprehensive Notes for the exam ( 36 pages long!)

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4 Dec 2017
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APST 207
FINAL EXAM
STUDY GUIDE
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Basic Concepts and Measurements
Statistics are a set of tools and techniques that allow us to collect,organize, and interpret
data and analyze the relationship between pieces of data
Numerical Information
What is data?
Data can be anything
Data comprised of variables
A variable is a characteristic or property we’re interested in
If variable is categorical, each answer categories are called classes or levels
Variable= gender Classes female/male/other
Variables describe experimental units (or cases) and vary by experimental units
(individuals, groups, companies, countries)
Variables come in two flavors
Qualitative variables are not-numerical (they only exist in discrete whole units and result
from descriptions)
Dichotomies (Male/Female, Pregnant/Noy
Categories ( Race, Class, Eye color)
Quantitative variables are numerical (they can be order or ranked- obtained by counting
or measuring and are discrete or continuous)
Discrete variables: can be assigned values like 1,2,3 4 and are accountable
Value is obtained by counting e.g # of students in a class
Continuous Variables can assume all values between 2 values
Value is obtained by measuring temperature, height, weight
Where do we get data?
Variables apply to experimental units or cases
We collect data so we can describe a population
The entire set of something = N
Normally collect samples of a population
A subset of a population = n
EXAMPLE: Population : automobiles with 4 wheels, Samples 20 autos from each maker
Samples
Representative: exhibiting characteristics typical or desired for the population of interest
Random every single case in the population had an equal chance (probability of being
chosen
EXAMPLES :U.S Census, Nation SUrvey of Growth
Two types of statistics
Descriptive Statistics
Only interested in describing a sample or summarizing information about the
sample
Measured of central tendency;measures of spread
Wealth/Life Expectancy
Inferential Statistics
We want to use the sample to make generalizations about the entire population
Estimated of parameters; testing of statistical hypotheses
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Influence of temperature on ice cream consumption and crime rates
Our data
Come in the form of variables
That are quantitative or qualitative
The variables come from experimental units or cases
That can be anything we want to observe or ask questions about
We normally collect a sample of experimental units (cases)
States describing just the sample are descriptive
Stats that use the sample to tell us something about the population are inferential
Why do we care ?
The type of variable we have (quantitative or qualitative ) determines the statistic we can
use
And how we represent the data
Population (inferential) and sample (descriptive) statistics are calculated a bit differently
Measurement
Measurement is the process of assigning numbers and/or values to variables that
describe experimental units (cases)
Measurement comes in different brands
Each one deals with a specific type of data and has its own uses (and pitfalls)
There are four scales
Nominal (qualitative-discrete)
Ordinal (quantitative-discrete)
Interval (quantitative-continuous)
Ratio (quantitative-continuous)
Discrete - either/or there is nothing “in between” example T-shirt size
Continuous- exist on a continum
Nominal
Sometimes are called “categorical” scale
Each answer possibility representa a different group or category (only names are
meaningful)
May be dichotomous (only 2 classes)
The answer categories are called classes
Exhaustive (account for every possibilty )
Mutually exclusive (you can only belong to )
There is nothing ordered or value-oriented about nominal variables
Maybe assigned number values for analysis. Male=0 Female =1
Ordinal
Rankings: tell you what order your cases come in, but the distance between 1st and 2nd
isn’t clear (adds order to the names)
EXAMPLE: in race C.J finished 1st, Josh finishes 2nd, and Toby finishes 3rd
We know the ranking but not by how much they beat each other.
Interval
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Document Summary

Statistics are a set of tools and techniques that allow us to collect,organize, and interpret data and analyze the relationship between pieces of data. A variable is a characteristic or property we"re interested in. If variable is categorical, each answer categories are called classes or levels. Variables describe experimental units (or cases) and vary by experimental units (individuals, groups, companies, countries) Qualitative variables are not-numerical (they only exist in discrete whole units and result from descriptions) Quantitative variables are numerical (they can be order or ranked- obtained by counting or measuring and are discrete or continuous) Discrete variables: can be assigned values like 1,2,3 4 and are accountable. Value is obtained by counting e. g # of students in a class. Continuous variables can assume all values between 2 values. Value is obtained by measuring temperature, height, weight. Variables apply to experimental units or cases. We collect data so we can describe a population. The entire set of something = n.

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