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psyc test 3 Flashcards

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1
Q

What is statistics?

A

A branch of mathematics devoted to the collection, compilation, display and interpretation of numerical data.

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2
Q

What are the two types of statistics?

A

Inferential and descriptive

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3
Q

What is descriptive statistics

A

Presenting, organizing and summarizing data

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4
Q

What is inferential statistics?

A

Drawing conclusions about a population based on data observed in a sample (hypothesis testing)

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5
Q

What do we need statistics for?

A

Description
Prediction
Causation

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6
Q

What is description?

A

aims to describe the prevalence of something (prevalence of heavy drinking)

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7
Q

What is Prediction?

A

aims to forecast likely outcomes

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8
Q

What is Causation?

A

aims to establish cause and effect

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9
Q

What are units? Where are they found?

A

the objects we are studying (people, companies, students)
Usually the rows in the data set

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10
Q

What are variables? Where are they found?

A

measurements that vary across people (height, weight)
Usually the columns

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11
Q

What is the dependent variable? What are other words for it?

A

The variable to be explained (outcome variable, response variable, primary endpoint)

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12
Q

What is the independent variable? What are other words for it?

A

Determinants of the dependent variable (explanatory variable, predictor variable, covariate)

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13
Q

What is the control variable? What is another word for it?

A

Any other variable that may plausibly alter the relationship between the IV and the DV (covariate)

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14
Q

What are the 4 types of measurements/ variables?

A

Nominal, ordinal, continuous- interval, continuous- ratio

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15
Q

What are nominal variables and give an example?

A

The data are categorized with no inherent order (hair colour)

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16
Q

What are ordinal variables and give an example?

A

The data are categorized and ranked (score on likert scale, year of university)

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17
Q

What is interval data and give an example?

A

Data that is continuous, ranked and evenly spaced (test scores)

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18
Q

What is ratio data and give an example?

A

Data is continuous, evenly spaced and has a natural zero (height)

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19
Q

What is the first step to describing data?

A

categories and sort it

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20
Q

What is a frequency table? And how are they formatted?

A

A table that lists each value and the number of times it appears

Tables are listed from highest to lowest value and each value is included even if tis frequency is zero

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21
Q

What is relative frequency?

A

proportion. dive the frequency by the total n

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22
Q

What are grouped frequency tables and why are they used?

A

Are data is too speed out (too many 0 frequencies). We create grouped intervals that has equal width and always start with a multiple of the width

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23
Q

What is a measure of central tendency? what are the measures of central tendency?

A

The value of a “typical” observation. Mean, mode, median

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24
Q

What is the mode?

A

most common value

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25
Q

What are the 4 types of modes you can have?

A

unimodal, bimodal, multimodal, amodal

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26
Q

What type of data can you use for median?

A

Since It has to be ordered it can only be used for ordinal, ration or interval

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27
Q

What type of data can you use for mean?

A

interval or ratio scales

28
Q

What types of data are the mean, median and mode most appropriate for

A

Mean is best for continuous
Median is best for ordinal
Mode is best for nominal

29
Q

What is a histogram?

A

Plots frequency data for continuous variables. The bars all touch and a space means there is no data for that value

30
Q

What is a bar chart? And what are they used for?

A

Used for ordinal or nominal data
Bars do not touch and represent categories. Shows the frequency. The order doesn’t matter for nominal

31
Q

When will the mode, median and mean all be the same

A

When the data is symmetrical and unimodal

32
Q

What happens if you have a skewed distribution?

A

The mean will be pulled towards the skew and the median will be between the mode and the mean

33
Q

What happens to the mean if there is an extreme skew (extreme outliers)

A

It is biased towards the outliers

34
Q

What type of skew extends out to the left

A

negative

35
Q

What type of skew extends out to the right

A

positive

36
Q

What are the measures of variability?

A

Range, SD, interquartile range

37
Q

What is the range?

A

Difference between the lowest and the highest score

38
Q

What is the inter-quartile range (IQR)

A

measure of variability in non-normally distributed data. Separates data into 4 equal parts and considers the different between the lower and upper quartile

39
Q

What is standard deviation?

A

measure of how close values are to the mean

40
Q

What does a low SD mean?

A

Values are close to the mean

41
Q

What does a high SD mean?

A

values are spread out

42
Q

What is an outlier? Are all extreme scores bad?

A

An extreme score that is much higher or lower than the rest of the scores. Some may be important to our data

43
Q

What can cause outliers?

A

errors, misunderstandings, equipment failures

44
Q

What are the mean, median and mode affected by outliers?

A

Mean is most sensitive and will be pulled towards the outlier

Median is not really impacted unless there are many outliers

Mode is not impacted

45
Q

How are the range and SD affected by outliers

A

SD will be larger
Range will be greatly impacted

46
Q

What is a z-score? What are the units?

A

How far an individual score is from the mean. Measures exactly how many standard deviations above or below the mean a data point is.

Z-score is standardized so it has no units

47
Q

What can Z scores be used for?

A

to determine if a value is an outlier or not

48
Q

What is the formula for Z-score?

A

z= (X-M)/SD

49
Q

Why is the normal distribution important

A

Statistical test assumptions
Method selection between parametric and non parametric methods
Data transformations

50
Q

What tests assume that data follows a normal distribution?

A

t-test, ANOVA

51
Q

What is parametric vs non-parametric methods?

A

Parametric assumes normality

52
Q

What is data transformation?

A

transforming data to meet normality assumptions

53
Q

What percentage of data is within 1 SD, 2SD, or 3 SD?

A

68% within 1SD
95% within 2SD
99.7 within 3 SD

54
Q

What is skewness

A

Whether the data is distributed symmetrically around the mean. Describes asymmetry of distribution

55
Q

What does 0 represent for skewness.
What does positive represent for skewness
What does negative represent for skewness?
Draw Skewness

A

0= perfect symmetry
negative = left skew
positive = right skew

56
Q

What is kurtosis?

A

whether data is peaked or flat. heaviness of a distributions tails relative to a normal distribution

57
Q

When is kurtosis high? when is it low?

A

high when data is near the mean
low when data is spread out

58
Q

What is Platykurtic
What is mesokurtic
What is leptokurtic?

A

<3 is platykurtic = flat
= 3 mesokurtic =normal
leptokurtic >3 = tall

59
Q

What the 2 ways to assess normality?

A

Visually or with statistical analyses

60
Q

What are the two ways to visually assess normality?

A

Using a histogram or Q-Q-plots

61
Q

What do Q-Q plots show?

A

If data is normal in a Q-Q test, the data will follow the diagonal line. If it is skewed it will deviate

62
Q

What are types of statistical analyses that can assess normality?

A

Skewness score
Kurtosis score
Shapiro Wilks for Normality

63
Q

What is Shapiro Wilks test for normality?

A

Means data is not significantly different from a normal distribution. Use p >.05 to

64
Q

What happens to power when there are more participants? What is the risk?

A

Power increases with more participants, it becomes more likely to detect small or subtle effects. This can also increase the likely hood of finding a false positive since there’s a greater sensitivity to detect any signal, whether it’s a true effect or just random noise.

65
Q

What should determine your distribution model?

A

The nature of the data and the phenomenon it represents

66
Q
A

chem (5 decks)

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