Data Analysis Test 1 UARK Pullen

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62 Terms

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Statistics

The science of collecting, organizing, analyzing, interpreting and presenting data

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Descriptive Statistics

The collection, organization, presentation and summary of data

ex) mean, median, mode

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Inferential Statistics

Generalizing from a sample to a population and making decisions

ex) 200 students = sample

entire student body = population

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Data Set

Collection of data values as a whole (what goes into excel)

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Observation

Each data value (goes into data sets)

ex) genders

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Subject (or individual)

An item for study

ex) an employee in your company

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Variable

A characteristic about the subject

ex) an employee's income or gender

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Data Type: Categorical/Nominal/Qualitative

Values are described by words rather than numbers

ex) gender, ethnicity

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Data Type: Numerical/Quantitative

Measuring a value

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Type of Numerical/Quantitative = Discrete

Countable number of values (integers or whole numbers)

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Type of Numerical/Quantitative = Continuous

Variable that can have any value in an interval value

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Ratio Data

Strongest type of data, has a definite zero and starting point (quantitative)

--> can add, subtract, multiple, divide, mean + STD

ex) GPA, money

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Interval Data

Second strongest type of data, a ranking with number associated/anything without a definite zero

--> can mean, STD but cannot add, subtract, multiple, divide

ex) 1-5 rating, temperature

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Ordinal Data

Third type of data, a ranking system without numbers associated with data

--> can do frequency counts or %

ex) year in school, excellent fair poor

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Nominal Data

Weakest type of data, straight words with no meaning behind the answers (qualitative)

--> can do frequency counts or %

ex) favorite food, gender, ethnicity

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Type of Data Set = time series data

each observation in the sample represents a different equally spaced point in time

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Type of Data Set = Cross sectional data

each observation represents a different individual unit (person) at the same point in time

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Univariate

one variable

(histograms, descriptive statistics)

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Bivariate

two variables

(scatter plots, 2 sample hypothesis, simple regression)

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Multivariate

more than two variables

(anova, multiple regression)

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Control group

the group that does not receive the experimental treatment

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Experiment group

exposed to manipulation of independent variable

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4 steps to construct a histogram

1) Find the min and max value

2) Define the # of bins/classes

3) Define the bin/class width

4) Define the upper limit

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How to find the min and max value

In excel: =min(data)

=max(data)

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How to define the # of bins/classes

its based on the # of observations (n)

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How to define the bin/class width

(max - min) / # of bins

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How to define the upper limit

It must be larger than the maximum value!

ex) max value = 676.42 width = 80

Make upper limit 680 then decrease by increments of 80

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How to find relative frequency

frequency # / total #

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how to find cumulative frequency

add each sum of preceding frequencies / total

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skewed left

mean < median < mode

negative #

<p>mean < median < mode </p><p>negative #</p>
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skewed right

mode < median < mean

positive #

<p>mode < median < mean </p><p>positive #</p>
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symmetric

mean = median = mode

skewness is close to zero

<p>mean = median = mode </p><p>skewness is close to zero</p>
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Modal class

class with the highest frequency

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Unimodal

one mode

<p>one mode</p>
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Bimodal

two modes

<p>two modes</p>
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Multimodal

more than two modes

<p>more than two modes</p>
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Mean

average

excel: =average(data)

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Median

Middle number

excel: =median(data)

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Mode

The value that occurs most frequently in a given data set

excel: =mode(data)

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Sample

statistic

portion of people

x-bar

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Population

parameter

whole number

mu

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Frequencies

number based off classes/bins

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Skew excel function

=skew(data)

--> < 0 = negative skewed

--> > 0 = positive skewed

--> = 0 = normal distribution

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Kurtosis

measures the peak/height of the curve of the distribution

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Leptokurtic

positive kurtosis

sharper rising peak; > 0

<p>positive kurtosis</p><p>sharper rising peak; > 0</p>
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Platykurtic

negative kurtosis

slower rising peak; < 0

<p>negative kurtosis</p><p>slower rising peak; < 0</p>
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Mesokurtic

normal distribution

= 0

<p>normal distribution</p><p>= 0</p>
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Kurtosis excel function

=kurt(data)

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Range equation

max - min

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Population variance equation

knowt flashcard image
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Population standard deviation equation

the square root of the population variance

<p>the square root of the population variance</p>
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Sample variance equation

knowt flashcard image
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sample standard deviation equation

the square root of the sample variance

<p>the square root of the sample variance</p>
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Population variance excel equation

=var.P(data)

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Sample variance excel equation

=var(data)

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Population standard deviation excel equation

=stdev.P(data)

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Sample standard deviation excel equation

=stdev(data)

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Trimmed mean

the mean of the data values left after "trimming" a specified percentage of the smallest and largest data values from the data set

--> 10% take off the lowest and highest values

--> 20% take off the lowest 2 and highest 2 values

KEEP WHOLE NUMBERS NOT % (like dont change 2% to .02 bc its wrong)

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growth rate equation

=(present / initial) ^1/(n-1) - 1

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Sharpe Ratio equation

(mean return - risk-free rate) / standard deviation return

(mean Xi - Rf) / std dev Si

--> you want the higher number

<p>(mean return - risk-free rate) / standard deviation return</p><p>(mean Xi - Rf) / std dev Si</p><p>--> you want the higher number</p>
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Sharpe Ratio

When looking at returns, look Xi values

When looking at risks, look at Si values

--> you want the higher number

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Empirical Rule

Total area = 1 or 100%

Only use when normal distribution!!!

<p>Total area = 1 or 100%</p><p>Only use when normal distribution!!!</p>