Midterm 1 Flashcards
Sample
smaller representation of the whole population
Population
pool of individuals from which a sample is drawn
Explain the difference between parameters and statistics
Parameters describe populations, statistics describe samples
Random sample
everyone in the population has a equal chance of being chosen
Convenience sample
People that are easier to access by the researcher are chosen
Bias
prejudiced results and strays away from the accurate value
Error
inaccurate results which is usually always present in a sample
Sampling error
randomness, statistical noise (when you increase sample size, sampling error decreases)
Sampling bias
when some members of the population are more likely to be chosen than others
Measurement error
Difference between the observed value and unobserved value
Measurement bias
When I collect data
Relate sampling and measurement bias to the concepts of internal and external validity
How well you control confound variables
How well your results reflect the entire population
Confidence Interval
Probability that a parameter falls between a set of values for a certain proportion
Explain the effect of increased sample size on confidence intervals.
Decreases the width of confidence interval as it decreases the standard error
Continuous
On a scale, changes over time
Mean
average
Categorical
discrete categories ex. sex/snowboard
Ordinal
rank order
Median
middle number
Mode
number that occurs the most
When are mean and median the same
normal distribution and if data is symmetrical
What is used as central tendency if data is skewed
median
Describe the probable sample effect on the range of a variable
The greater your sample size the larger the range
Explain how quantiles can be used to measure variance
Used to calculate interquartile range (variability around the median)
Calculated as the third quartile - first quartile
Explain the probable sample effect on the interquartile range
As sample size increases, variance decreases
Explain how standard deviation is calculated
The square root of variance by determining each points deviation from the mean
Coefficient of Variation
standard deviation over mean of the population to show variability
Confidence interval on the mean
provides a upper and lower limit, and tells us how much uncertainty there is
Explain what a standard error on the mean measures
Measures the discrepancy between the sample mean and population mean
Describe what sample size effects have on the SEM
As sample size increases SEM decreases
Identify three assumptions made in calculating SEM
Random sample
Independent observations
Accurate data not biased
Explain what t measures
How closely distribution of data measures distribution predicted under the null hypothesis
Correctly define what a p value measures
The probability of obtaining observed results assuming that null hypothesis is true
Effect size
how meaningful the relationship between variables was
NHST
non-hypothesis significant testing (testing to check significance between two variables assuming the null hypothesis is true)
type 1 error
rejecting the null hypothesis when its true
Type 2 error:
not rejecting the null hypothesis when its false
Residual
difference between observed and expected values
Assumptions of a Pearson product-moment correlation
Random sample
Independent observations
Linear relationship
No outliers
normal distribution
What a coefficient of correlation measures
Direction and strength of linear relationship between two variables
