Final Flashcards by Rachel Wheeler

What is the “who”

Study units or simply who the subjects or participants are

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Sample

representative sample of a target population

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parameter

measure of a population

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statistic

measure of a sample

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explanatory or predictor variables

independent variables

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response variable

dependent variable

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extraneous variables

explanatory variables that are not of interest that could affect the response variable

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systematic sampling

First-person is selected randomly

Then Every [period of time]

Then Every nth person

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Stratified vs cluster

Stratified: Population is divided into groups based on prior information. Then within each group random sampling is done. Alberta example

Cluster: Randomly select groups of people and then all people within these groups are interviewed.

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Voluntary response bias

Asking for volunteers but people who like something are more likely to volunteer

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Response bias

Loaded questions: Questions suggest or prompt a particular response favored by the researcher

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Nonresponse bias

Large amount of people fail to respond to questions

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Difference between observational and experimental studies

In observational studies, there is no manipulation or control of variables/conditions. In experiments there is deliberate manipulation of explanatory variables

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Observational studies population and casual inferences

Population inferences: Can be made with random selection

Casual Inferences: Can NOT be made as there is too many extraneous variables. cause and effect cannot be made

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Experimental studies population and causal inferences

Both can be made if there is random selection and random assignment

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Relative frequency

Frequency divided by total number of observations

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Pie Chart

Frequency of categorical data

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Bar Graph

show the frequencies for one variable

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Marginal and joint distribution

Marginal: Total frequency for each variable

Joint: Frequency of joint event

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Conditional distribution

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Negative skew vs positive skew

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Median and mean resistance

Median is resistant to extreme values or skewness

Mean: is NOT resistant because it is influenced by skewness

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Skewed distribution best measure of centre and spread

Centre: Median

Spread: Quartiles

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Symmetric distributions best measure of centre and spread

Centre: Mean

Spread: Standard deviation

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Mean mode and median in right/positive skewed

Mode < Median < Mean RODE

Mean mode ande median in left/negative skewed

Mean < Median < Mode

If there is an odd set of observations is the median included

Boxplots parts

Population standard deviation

Boxplots skew

Quartiles skew

Probability for at least one

Sample size for normal distribution

>30

between a small sample and a large sample, when sampling is taken, which has more variability

smaller sample has more variability

Calculating quartiles

height calculation for a uniform distribution

The variance between two values

finding z or probability for sample mean

probability or z score for a sample proportion

assumption of normality for proportion

central limit theory

mean for two points

Probability between two points sometimes on a rectangle

This finds the actual probability not the z score

Type I error

Accidently rejecting null hypothesis You thought there was a difference when there wasn't one Alpha

Type II error

Not rejecting the null hypothesis when you should have You thought there was no difference when there was one beta

To reject the null hypothesis is p greater then or less than alpha

What does alpha mean

The maximum probability of the type I error that you will allow for

what does the p value mean

Observed probability of a type 1 error that you will find

Margin of error one proportion

What does the p value mean in proportions

When to reject the null hypothesis in a one-population proportion test

the **hypothesized** proportion is not within the confidence interval

Determining sample size

two population proportions rejecting the null hypothesis

Chi squared expected frequency calculation

when do you double the p-value

in z score when it is two tailed don't forget to subtract from 1 if its positive

How to calculate margin of error

alpha/2 multiplied by SE so confidence interval without estimate

When to reject the null hypothesis for one population mean

what does sp mean

pooled standard deviation

when to use paired t test

Ecological monitoring Medical measurements from the same patient Taking measurements from the same area

what does k and n mean in anova

k means number of populations n means total number of observations (x)

how to find pooled standard deviation in anova

How to find F statistic in ANOVA

on formula sheet mean square of between groups ___________________________________ means square of within groups

relationship between sum of squares, df, and mean square

What does a linear regression measure

relationship between two quantitative variables

How to determine the strength of a linear relationship

r close to -1 or 1 means a strong linear relationship r close to 0 indicates none or weak relationship

how to calculate r

units of r

no units as they cancel out during calculations

interpolation vs extrapolation

coefficient of determination

r squared

How to tell if two events are independent

If P(A∩B) is the same as P(A) times P(B) then the events are independent

Chi square tests

Chi square independence test hypothesis

Assumptions for a one/two proportion z test

1. All samples are taken independently 2. The number of failures and successes are both at least 10

Properties of chi square curves

one tailed always positive

CHi square assumptions

1. simple random sampling 2. indpendent sample 3. sample size should be no more than 10% of population 4. all expected frequencies are at least 5

properties of a t-curve

margin of error and sample size

inversely proportional

Properties of a F curve

Disjoint

Events are considered disjoint if they never occur at the same time; these are also known as mutually exclusive events. Events are considered independent if they are unrelated.

The level of significance in a hypothesis test is?

The probabililty of rejecting a null hypothesis when it is in fact true