1] Introduction Flashcards
Statistics is the science of……data
1: Collecting
2: Organising
3: Presenting
4: Analysing
5: Interpreting
What is data
Pieces of information we can use
Why do we collect data
So we can analyse the data in order to help us understand and answer a specific research question
What is statistics in psychology for
These are tools that help us research and understand a psychological phenomenon
Examples of when we can use statistics
1] Insurance
Companies use statistical analysis to calculate rates in homes, health, life insurance and motor vehicles.
2] Goverment
They use statistical data to determine the decisions and type of policies to put in place
What is a variable
It is any measured characteristic that differs from subject to subject
E.g: Height, gender, mental health
What are the two types of variables
1: Categorical (non numerical data)
2: Numerical/Quantatuve
What are the two subgroups of categorical/quantitative variables
1: Discrete
2: Continuous
What is categorical variables
This is data that can separated into specific categories but they cannot be ordered or measured
E.g: Hair colour, gender, political affiliation
What is numerical variables
These are variables that measure values to describe its quantity and can be ordered in a certain mannner
E.g: Heart rate, total rainfall
Numerical: What is a discrete variable
It’s a variable that takes in a distinct countable value
E.g: The number of pregnancies, number of needles, score form 0-10
Numerical: What is a continuous variable
A random variable that can take on an infinite number of values within a certain range and it is not countable
E.g: Temperature, length, a concentration
What are the four levels of measurement/types of data
[Categorical]
1: Nominal data
2: Ordinal data
[Numerical]
1: Interval data
2: Ratio data
What does the level of measurement do
It dictates what type of statistical analysis can be conducted with that data
What is nominal data
This is when you can label and name variables without any quantitative value
There is no ordering of items implied
They can be classified and counted but cannot be added, subtracted, multiplied or divided in a meaningful way
E.g: Nationality, gender, degree type
What is ordinal data
This is a form in ranked data that has sets of labels or names that have relative values and they typically measure non numerical concepts
The order of the values is meaningful but we do not know the distinct difference between each point in the scale
E.g: Satisfaction ratings
What is interval data
Thus when we know the order and difference between the values on a numerical scale, the difference between each all have the same measurement
It does not have an absolute 0 and it can be added or subtracted but not multiplied or divided
E.g: Temperature in degrees, IQ
What is ratio data
It tells us about the order, the difference between each value and has an absolute 0 included so it provides us with the most information
They can send added, subtracted, multiplied and divided
E.g: Weight, income, height, market share
The difference between interval and ratio data
Ratio: the variables will never fall below 0
E.g: You can have a negative height
Interval: the variables can fall below 0
E.g: Temperature can be negative (-1)
