# Empirical Research

Autor: H. Opitz • May 17, 2017 • Coursework • 15,702 Words (63 Pages) • 17 Views

**Page 1 of 63**

Empirial Research Methods Lecture 1

Measurement

Level of Measurement: relationship between the numbers and waht is being measured

→ Why is it important? Eg. Age → Adult (yes/no) ,Age groups ( 1-12, 11-20…)

Measurement Scales

Binary: Two distinct categories (Male/female, yes/no)

Nominal: - More than two categories

- Number only tells category
- No ranking
- E.g. colours, means of transportation
- Pointless to arithmetic

Ordinal: - Ordered categories (logical order)

-Tells nothing about differences between values

-E.g. 1st, 2nd, and 3rd prize

Interval: - Information about differences between points on a scale

- Equal intervals represent equal differences
- E.g. Celsius scale

Ratio: -Same, but with absolute zero

-e.g. weight

→ What matters: you cannot perform all calculations on all variables

Basic Issues in Measurement

Validity:

- Extent to which a measure correctly represents the concept of study

- Internal: How well the study was done
- External: Generalize results to other situations

Accuracy:

- Measure close to actual value
- Getting the ‘right’ answer on average

Reliability:

- Extent to which a variable is consistent in what it is intended to measure

LOOK AT IT AGAIN, JUST HALF OF THE LECTURE

Lecture 2

The Research Process

- Research Question

- Observe the world

- Theory/literature
- Hypothesis/prediction

- Variables

- Collect Data

- Measurement (Lecture 1)

- Analyze Data

- Graphically/ descriptively ← L2
- Fit a model

- And back to the beginning

Descriptive/summary statistics

Step #1

Quantitative description of main features of data

Just a summary

Before actual analysis

→ Which are the players of the game?

Which is the nature of the variables? (Discrete, continuous)

Do you see any problems? Things to keep in mind? (e.g. range, negative values)

→ Get a feel for your data

Summary Statistics

- Number of observations

- Measures of central tendency

- Mean: arithmetic average (influenced by extreme observations

- Median: middle point when values are ranked in order of magnitude (Relatively unaffected by extreme scores)

- Mode: most frequent value (More than one mode, e.g. bimodal, multimodal)

→ Which measure of central tendency to use?

Type of Variable | Best measure of central tendency |

Nominal | Mode |

Ordinal | Median |

Interval/Ratio (not skewed) | Mean |

Interval/ Ratio (skewed) | Median |

- Skewness

- Says something about the shape of the distribution

- Deviation from normal (Normal: skew=0)

- Symmetry of a distribution, compared to a normal

- Kind of skew labelled according to the longer tail

- Values outside the -1 to +1 range indicate a substantially skewed distribution

[pic 1]

- Kurtosis

- Says something about the shape of the distribution

- Deviation from normal (normal/mesokurtic: Kurtosis=3)

- Degree to which scores cluster at the tails and how pointy a distribution is (peakedness of flatness), compared to a normal

- Leptokurtic: heavy tails and pointy (>3)

- Platykurtic: light tails and flatter (<3)

[pic 2] [pic 3]

5. Minimum and Maximum

-Range

Dispersion

Defined as: maximum value – minimum value

Affected by extreme score

-Interquartile Range

Dispersion

Q1: lower quartile (25%)

Q2: upper quartile (75%)

- Variance and standard deviation

Dispersion

- Variance
- Standard deviation

- Square root of variance
- How spread out the data are from the mean
- Heterogeneity of the sample

- ‘normal’ data (bell-shaped)

[pic 4]

Measure of association

-Sometimes part of summary statistics

-Correlation/Correlation coefficient

- Strength of the relationship between two variables

-Positive or negative(sign)

- (-1, +1)

-Magnitude says something about the strength of the relationship (size)

-Coefficient of +1 (-1):

-Two variables are perfectly positively (negatively) correlated

-As one increases, the other increases (decreases) by a proportionate amount

-Coefficient of 0:

-No linear relationship between two variables

- As one variable changes, the other stays the same

-Significance

...