05 - basic statistics concepts Flashcards
Why we need statistics (2 reasons)
OBJECTIVE way of interpreting a collection of observations
REDUCE data to useful value that represents a trait about the data
Categorical measurements
Qualitative
( “which type” and “which category”)
Continuous measurements
Quantitative
“how much” and “how many”
4 different scales of measurement
Nominal
Ordinal
Interval
Ratio
Which 2 scales are categorical
Nominal
Ordinal
Which 2 scales are continuous
Interval
Ratio
Nominal scale
“Name”
Associated with categorial data
Ordinal scale
“Order”
Associated with categorical data
Any rank ordering
Limitation of ordinal scale
Don’t always know the amount of difference between each piece of data
Interval scale
“equal intervals”
Associated with continuous data
Has all the properties of ordinal data plus equality of units
May contain an arbitrary zeron
Ratio scale
Ratio statements can be made
Associated with continuous data
Has all the properties of interval scale plus an absolute zero
What is an arbitrary zero?
Does not reflect the absence of the trait being measured
What is an absolute zero?
Absence of the trait
Summary - nominal
Values are named
Summary - ordinal
Values are named and ordered
Summary - interval
Values are named and ordered and have equal intervals
Summary - Ratio
Values are named and ordered and have equal intervals and have an absolute zero
Statistical foundations of measurements theory (7)
- Frequency distribution
- Mean
- Variance
- Standard deviation
- Normal curve
- Correlation coefficient
- Standard error of measurements
What is frequency distribution?
Number of times each scores is represented in the data set
What is mean?
Sum of the observation divided by the number of observations
What is variance?
Measure of variability of the data set
What is standard deviation?
Square root of the variance
What is normal curve?
Symmetric frequency distribution
Z-score
What is correlation coefficient?
The degree of linear relationship between two variables
