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ASU / Economics / ECN 221 / What is the definition of discrete data?

What is the definition of discrete data?

What is the definition of discrete data?

Description

School: Arizona State University
Department: Economics
Course: BUSINESS STATISTICS
Professor: Stefan ruediger
Term: Spring 2017
Tags: Statistics
Cost: 50
Name: Study Guide for Exam 1
Description: These notes cover what will be on our exam from chapters 1-3. I have included a majority of the formulas as well
Uploaded: 02/05/2017
4 Pages 185 Views 1 Unlocks
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Exam 1: ECN 221Don't forget about the age old question of What defines a philosopher?

We also discuss several other topics like What are the three basic trade offs faced by a society?

Types of DataDon't forget about the age old question of What is the difference between arithmetic and algebra?
Don't forget about the age old question of How do citizens exercise their authority in a republic?

✦ Qualitative (Descriptive)

  • Nominal
  • No ranking allowed
  • Data are labels or names
  • Can be numeric or non-numeric
  • Zip codes, home ownership
  • Ordinal
  • Ranking allowed
  • Can be numeric or non-numeric
  • No measurable meaning to number diff.
  • Credit score, education level

If you want to learn more check out How does axial stress vary from neutral axis?

✦ Quantitative (Numerical Data)

  • Interval
  • Ranking allowed
  • Interval diff. is meaningful
  • No true 0 point
  • Always numeric
  • GPA, temperature
  • Ratio
  • All characteristics of Interval data
  • Ratio of two values is meaningful
  • True 0 point
  • income

If you want to learn more check out What is the meaning of london forces in intermolecular interactions?

                US        AZ        CA

2009                                        ← cross sectional: values collected during

2010                                                a single time period

2011                      ← time series - valued collected over a range of time period

2012                                                                Population

                                                                       =

Descriptive ⇒ summarize                                        Parameter

Inferential ⇒ making statements                                 population        

by examining sample results                                

sample

                                                        

                                                                Sample

                                                                    =

                                                                Statistic

Sample: 0        2        2        1        4        3        3        5        5        0        

Frequency

Rel. Freq.

Cum. Rel. Freq

0

2

0.2

1

1

2

2

3

2

4

1

5

2

                                                                

Discrete Data: values that can be counted

                ex) 0, 1, 2, 3… children, vacation days

        vs.

Continuous Data: values that take on any real number (including decimal points)

                ex) time, weight

Class width: solve for

        Where        

                

        Est. class width:

        Example:        

                        

                        

                        

        Class width:

Measures of Central

Tendency

|一一一一一一一一一一一一|一一一一一一一一一一一一|

Mean                        Median                        Mode

  • Mean - generally use if there are no outliers
  • Sample ()
  • Population (μ)
  • Median - use if there are outliers
  • Index point
  • If not whole round up
  • When n is even, median =

  • Mode - if the data is categorical
  • The value that occurs most often

  • Z-score:
  •  or

Distribution Shape

  • Symmetric (mean = median)

        

  • Skewed

Left (mean<median)                        Right (mean>median)

                                

Measures of Variability

  • Range
  • Largest value - smallest value
  • Variance
  • Sample:
  • Population
  • Standard deviation
  • Sample =
  • Population =

  • Coefficient of Variation (CV)
  •  or

Empirical Rule

Measure of Relative Position

  • Percentiles
  • Where
  • Quartiles

Measures of Association

  • Covariance
  • Correlation
  • Indicates strength and relationship between 2 variables
  • Ranges from -1 to +1
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