Inference Flashcards
What is a latent variable?
Latent variables are things that are not directly measurable such as attitudes, beliefs, perceptions and so on.
What is psychometrics? And Galton’s theory
Psychometrics is the field of study concerned with
psychological measurement. Psychometrics are concerned with measuring latent variables. In order to measure latent variables, which are not directly observable, we measure a co-related observable variable which allows us to draw inferences. These co-related variables are referred to as ‘items’. An example would be measuring aggression, the item would be seeing if someone uses violence.
When we look at a sample and take the mean/SD/SE/etc. we are are looking at …….
However, when we look at a whole population’s mean/SD/SE/etc. we are looking at ……….
Statistics
Parameters
The statistic is the estimator of the model parameter
How can a statistic and a parameter be distinguished visually?
Statistic uses latin symbols
Parameter uses greek symbols
Why is it that 3 different samples will have different means? Why would each mean from each different sample, but different to the population mean?
This is due to ‘random error’
If we are looking at ‘how often do people exercise per week’ and we take a sample of people on the street. However, we are taking this sample on the street but outside of a gym. Why would this sample have a different mean to the population mean?
This is due to a systematic error! This is a bias sample
When we describe data, if there is a small random error this means our data is more ….
If there is a small systematic error this means our data is more …..
- small random error - more reliable
2. small systematic error - more valid
What do we mean by ‘reliability’?
Every time you reproduce the same test, you will receive the same result. The reproducibility of a result. Reliability is about the reproducibility, the consistency, and the precision of a measurement.
What do we mean by ‘validity’?
The validity is our ability to compare the result to a ‘gold standard’, and if it is close to this gold standard then it is valid (accurate). Validity is about the accuracy of the measurement, based on the current knowledge.
Are results always valid and reliable at the same time?
No - A result can never be valid without also being reliable.
However, a result can be reliable but does not mean it is valid (e.g. could get the same result 100 times, but the scales you are using to measure are wrong).
What are the key features of random error? And, what does it mean if the random error is small?
- Unpredictable
- It can go up or down on either side
- It is due to completely random factors
- If small, it is more RELIABLE
What are the key features of systematic error? And, what does it mean if the systematic error is small?
- Consistent
- You always underestimate or overestimate the true value
- Due to factors which can be traced
- If small, then we have more VALIDITY
What is the ‘sampling distribution of the mean’? (if normally distributed, random error)
The sampling distribution is the distribution of multiple sample’s mean. It is the “distribution of the estimated means from different samples”
How does the sampling distribution of the mean fit into the central limit theorem? (if normally distributed, random error)
Theory states that if we take more and more and more samples from the same population, then the sampling distribution of the statistic mean will be a normal distribution
What is the mean of the sampling distribution? (if normally distributed, random error)
The mean of the sampling distribution is the mean of the population which the sample came from. The mean of all the sample means is the population mean! All sample means should come under this population mean.
