Basic Data Analysis: Descriptive Statistics

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Basic Data AnalysisDescriptive Statistics
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Disposition for afrapportering

• Om undersøgelsens tilblivelse
• Undersøgelsens hovedresultater
• Materialets sammensætning
• Elevernes faglige profiler
• Mhp. en bestemt videreuddannelse?
• Supplering inden studiestart?
• Hvad skal der ske efter sommerferien?
• Faglige interesset
• Opdelt på hum, samf og tek-nat hovedområder
• Kriterier for valg af studium
• Faglige dimensioner
• Sociale dimensioner
• Praktiske forhold

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Disposition for afrapportering(fortsat)

• Valg af studieby
• Plan for valg
• Opfattelsen af forskellige studiebyer
• Alt-i-alt-vurdering af studiebyer
• Om matematik-økonomi-uddannelsen
• Hørt om denne
• Kendskab til, hvor man kan få uddannelsen
• Overvejet at påbegynde mat-øk?
• Specielt om studiet ved AAU
• Kendskab
• Kílde til kendskab
• Påbegyndelse af studium?
• Sandsynligheden for at begynde efter
  sommerferien.

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Types of Statistical Analyses Used in Marketing
Research

• Data summarization the process of describing a
  data matrix by computing a small number of
  measures that characterize the data set
• Four functions of data summarization
• Summarizes the data
• Applies understandable conceptualizations
• Communicates underlying patterns
• Generalizes sample findings to the population

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Types of Statistical Analyses Used in Marketing
Research
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Types of Statistical Analyses Used in Marketing
Research

• Five Types of Statistical Analysis
• Descriptive analysis used to describe the data
  set
• Inferential analysis used to generate
  conclusions about the populations
  characteristics based on the sample data
• Differences analysis used to compare the mean of
  the responses of one group to that of another
  group
• Associative analysis determines the strength and
  direction of relationships between two or more
  variables
• Predictive analysis allows one to make forecasts
  for future events

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Types of Statistical Analyses Used in Marketing
Research
Hvis vi ændrer en bys image på en række
dimensioner, hvor meget stiger vurderingen af
byen så med?
Hvis vi ændrer en bys image på én dimension, hvor
meget stiger alt andet lige - vurderingen af
byen så med?
Hvilken betydning haropfattelsen af studiebyer
for valget heraf?

• Test af sammenhænge mellem
• undersøgelsesspørgsmål og kriterier
• undersøgelsesspørgsmål indbyrdes

Vurdering af repræsentativitet fx ved test mod en
kendt populationsfordeling på køn og alder

• Materialets sammensætning
• kriterier som køn og alder
• undersøgelsesspørgsmål

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Understanding Data Via Descriptive Analysis

• Two sets of descriptive measures
• Measures of central tendency used to report a
  single piece of information that describes the
  most typical response to a question
• Measures of variability used to reveal the
  typical difference between the values in a set of
  values

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Understanding Data Via Descriptive Analysis

• Measures of Central Tendency
• Mode the value in a string of numbers that
  occurs most often
• Median the value whose occurrence lies in the
  middle of a set of ordered values
• Mean sometimes referred to as the arithmetic
  mean the average value characterizing a set of
  numbers

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Understanding Data Via Descriptive Analysis

• Measures of Variability
• Frequency distribution reveals the number
  (percent) of occurrences of each number or set of
  numbers
• Range identifies the maximum and minimum values
  in a set of numbers
• Standard deviation indicates the degree of
  variation in a way that can be translated into a
  bell-shaped curve distribution

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Understanding Data Via Descriptive Analysis

• Measures of Variability

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When to Use a Particular Statistic
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Hvornår bruges hvad?Eksempler fra casen
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Datamatricen i Studievalgsundersøgelsen
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Hvornår bruges hvad?Eksempler fra casen
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Hvornår bruges hvad?Eksempler fra casen
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Hvornår bruges hvad?Eksempler fra casen
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Hvornår bruges hvad?Eksempler fra casen
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Hvornår bruges hvad?Eksempler fra casen
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Generalizing a Samples Findings to Its
Population and Testing Hypotheses About Percents
and Means
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Statistics Versus Parameters

• Statistics values that are computed from
  information provided by a sample
• Parameters values that are computed from a
  complete census which are considered to be
  precise and valid measures of the population
• Parameters represent what we wish to know about
  a population. Statistics are used to estimate
  population parameters.

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The Concepts of Inference and Statistical
Inference

• Inference drawing a conclusion based on some
  evidence
• Statistical inference a set of procedures in
  which the sample size and sample statistics are
  used to make estimates of population parameters

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Parameter Estimation

• Parameter estimation the process of using sample
  information to compute an interval that describes
  the range of values of a parameter such as the
  population mean or population percentage is
  likely to take on

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Parameter Estimation

• Parameter estimation involves three values
• Sample statistic (mean or percentage generated
  from sample data)
• Standard error (variance divided by sample size
  formula for standard error of the mean and
  another formula for standard error of the
  percentage)
• Confidence interval (gives us a range within
  which a sample statistic will fall if we were to
  repeat the study many times over

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Parameter Estimation

• Standard error while there are two formulas, one
  for a percentage and the other for a mean, both
  formulas have a measure of variability divided by
  sample size. Given the sample size, the more
  variability, the greater the standard error.

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Standard Error of the Mean
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Standard Error of the Percentage
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Parameter Estimation

• Confidence intervals the degree of accuracy
  desired by the researcher and stipulated as a
  level of confidence in the form of a percentage
• Most commonly used level of confidence 95
  corresponding to 1.96 standard errors

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Parameter Estimation

• What does this mean? It means that we can say
  that if we did our study over 100 times, we can
  determine a range within which the sample
  statistic will fall 95 times out of 100 (95
  level of confidence). This gives us confidence
  that the real population value falls within this
  range.

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Hypothesis Testing

• Hypothesis an expectation of what the population
  parameter value is
• Hypothesis testing a statistical procedure used
  to accept or reject the hypothesis based on
  sample information
• Intuitive hypothesis testing when someone uses
  something he or she has observed to see if it
  agrees with or refutes his or her belief about
  that topic

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Hypothesis Testing

• Statistical hypothesis testing
• Begin with a statement about what you believe
  exists in the population
• Draw a random sample and determine the sample
  statistic
• Compare the statistic to the hypothesized
  parameter

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Hypothesis Testing

• Statistical hypothesis testing
• Decide whether the sample supports the original
  hypothesis
• If the sample does not support the hypothesis,
  revise the hypothesis to be consistent with the
  samples statistic

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What is a Statistical Hypothesis?

• A hypothesis is what someone expects (or
  hypothesizes) the population percent or the
  average to be.
• If your hypothesis is correct, it will fall in
  the confidence interval (known as supported).
• If your hypothesis is incorrect, it will fall
  outside the confidence interval (known as not
  supported)

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How to Test Statistical Hypothesis
2.5
2.5
95
1.96
-1.96
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Types of Statistical Analyses Used in Marketing
Research

• Test af sammenhænge mellem
• undersøgelsesspørgsmål og kriterier
• undersøgelsesspørgsmål indbyrdes

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Sammenligning af to populationer i
Studievalgsundersøgelsen

• Sammenligninger ved hjælp af tabelanalyse

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Sammenligning af to populationer i
Studievalgsundersøgelsen
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Sammenligning af to populationer i
Studievalgsundersøgelsen
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Sammenligning af gennemsnittet for to spørgsmål i
Studievalgsundersøgelsen
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Sammenligning af gennemsnittet for flere end to
populationer i Studievalgsundersøgelsen
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