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U1 Psychology Stats 305 > Session 1 > Flashcards

Session 1 Flashcards

1
Q

what is a Population

A

All entities or individuals of interest

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2
Q

what is the point of a population

A

We often want to learn something about the population

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3
Q

what are Parameters

A

A value that describes the population

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4
Q

what is the symbol for population mean

A

Population mean, μ

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5
Q

what is the symbol for population variance

A

Population variance, σ2

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6
Q

what is Sample

A

A subset of individuals from the population aka Data that we will examine

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7
Q

what does N refer to

A

usually refers to sample size

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8
Q

what is an Estimate

A

A value that describes the sample

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9
Q

what is the symbol for sample mean

A

Sample mean, X (bar on top)

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10
Q

what is the symbol for sample variance

A

Sample variance, s2

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11
Q

what are the 2 types of stats

A

Descriptive Statistics and Inferential Statistics

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12
Q

what is Descriptive Statistics

A

Summarize/describe properties of the sample (or the population if we gather data from the entire population)

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13
Q

what is inferential stats

A

Draw conclusions/inferences regarding the properties of the population, but based only on sample data

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14
Q

what is a Variable

A

A characteristic that varies across observations (people, location, time, etc.)
aka Often a single column in our dataset

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15
Q

wha are Variables also known as

A

levels of measurements

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16
Q

what are the two types of variables

A

Quantitative and Categorical

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17
Q

what are types ofRatio 􏰀

Interval Quantitative variables

A

Ratio 􏰀

Interval

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18
Q

what are the types of Categorical variables

A

Ordinal 􏰀

Nominal

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19
Q

what is Nominal variable

A

Classifies objects

aka Are two observations the same or different on some attribute?
Not quantitative, though we can use numbers to index the categories

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20
Q 
what kind of variables are being used here: 
Which restaurant do you prefer?
Tim Horton’s
Burger King 
Thai Express
A

nominal

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21
Q

Gender
Country of Birth Native Language

these are all examples of what kind of variables

A

nominal

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22
Q

what does Dichotomous (binary) mean

A

Two categories/levels

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23
Q

how many levels in nominal variables

A

2 (Dichotomous (binary))

e.g Treatment/control Correct/incorrect

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24
Q

ranks the variables from highest level of measurement to lowest level of measurement

A

Ratio 􏰀
Interval

Ordinal 􏰀
Nominal

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25
what is Ordinal
Rank data aka Does one observation have more or less of an attribute than a second observation? Relative standing of two observations on the attribute Does not say by how much the observations differ
26
``` Birth order (1st, 2nd, 3rd) Students’ standing in class relative to others Importance of personal values ``` these are examples of what kind of variables
ordinal
27
what is Interval
Rating data (equal distances) aka Assigned numbers have meaningful units, and these unit sizes remain constant
28
Temperature (when measured using Celsius or Fahrenheit) Calendar year these are examples of what kind of variables
intervals
29
what is Ratio
Interval, with an absolute 0 point or meaningful origin aka 0 means lack of the attribute Comparisons such as “2 times as much” of something or “half as much” make sense
30
Height (feet, inches, meters), weight, elapsed time, pulse rate, car speed, price ($) these are examples of what kind of data
ratio
31
what are they 2 types of variable
``` Independent Variable (IV) Dependent Variable (DV) ```
32
what is Independent Variable (IV)
PredictOR (or covariate) | Factors in an experimental design
33
what is Dependent Variable (DV)
Outcome/Response | PredictED variables
34
what are the Types of Research
Correlational vs. Experimental Between-subjects vs. within-subjects
35
what is the Correlational IV measured by
the researcher
36
what is Correlational good for
Good for ecological validity - generalizing research findings to the real world
37
what is Correlational not good for
Not good for inferring causality; IV and DV may have a relationship due to a third (confounding) variable or common cause
38
what is done to the IV in Experimental
IV is manipulated by the researcher
39
what is experimental good for
Good for inferring causality
40
what is experiment not good for
Manipulating IV in lab settings may sometimes feel detached from the real world
41
Statistical methods to analyze data may be ________ for correlational and experimental designs Some data examples used in this course may be correlational
the same/similar
42
what is Between-subjects design (research)
Each participant in only one experimental condition (e.g., control or treatment)
43
with Between-subjects design , If random assignment is used what should happen to the groups
groups should be approximately equal on any confounding variables
44
what is Within-subjects design
Each participant does more than one experimental conditions (e.g., control and treatment) aka DV measured multiple times
45
what must researchers be careful about with Within-subjects design
Vulerable to practice effects and fatigue/boredom effects as alternative explanations for differences betwen conditions
46
what is Counterbalancing
used to help rule out alternative explanations Counterbalancing is usually thought of as a method for controlling order effects in a repeated measures design (see the notes on variance and experimental design). In a counterbalanced design to control for order effects, we use separate groups of subjects, each group receiving treatments in a different order.
47
what type of research is Counterbalancing used for
Within-subjects design
48
In this course, We focus on the relationships between how many IV and DV
one/multiple independent variables (IV) and one dependent variable (DV)
49
what is consistent about the DV
continuous (usually normally distributed)
50
what is consistent about the IV
Categorical/continuous
51
what is the point of Models in statistics
Summarize/describe a large amount of data with just a few numbers
52
what is the equation for the stat model according to field
Outcomei = (Model) + Errori
53
explain the parts to the model in statistics according to field
i subscript used to indicate a participant i Outcome - the DV Model - systematic part explained by IV1 Error - unsystematic part that is not explained by IV
54
what are Descriptive Statistics
Describe properties of samples (or populations, if completely known)
55
what kind of properties are described with descriptive stats
How are the data distributed? Where is the centre? How much variability is there in scores? What shape is the distribution?
56
what is used to describe 'centre
central tendency
57
what is in central tendency
Mean Median Mode
58
what is used to describe variability
variation
59
what is in variation
Range Variance Standard Deviation
60
what is used to describe shape of distribution
shape
61
what is in shape
Skewness Kurtosis
62
what is Mean
the average
63
The mean is vulernable to what
extreme values (outliers)
64
what is Median
the value in the middle
65
is the median vulnerable to outliers
The median is less vulnerable to extreme values (outliers)
66
what is Mode
The value that occurs most frequently
67
is the mode impacted by outliers
Not affected by extreme values
68
what is mode used for
Used for either numerical or categorical data
69
how many modes might there be
There may be no mode | There may be several modes
70
Mean is most commonly used when
always unless extreme values (outliers) exist
71
when is the Median used
often used if extreme outliers are present
72
when is the Mode used
is often used with categorical (nominal) data
73
what are Measures of variation
Measures of variation give information on the spread or variability of data values
74
what are the ways to measure variation
Range Variance Standard deviation
75
what is Range
Simplest measure of dispersion | Difference between the largest and the smallest observations:
76
what is Variance
(Approximate) average of ‘squared’ deviations of values from the mean
77
what is the equation for sample variance
s^2 = SS / N-1 = (Xi −X)^2/N-1
78
explain the parts to the variance equation
X = mean N = sample size Xi = ith value of the variable X SS = 􏰁Xi − X)2 = Sum of Squares (sum of squared deviations)
79
what is Standard deviation used for
Most commonly used measure of variation
80
what does standard variation show
variation about the mean
81
what units does SD have
Has same units as the original data
82
how to get the SD
Square root of variance
83
what does the Shape of a Distribution explain
Also describes how data are distributed Symmetric or skewed
84
what is skewed
Which way does the “tail” point?
85
what are the types of skewness
left symmetric right
86
what is another name for Normal Distribution
Gaussian or bell-shaped
87
In many statistical techniques for experimental designs, the dependent variable is assumed to be what
continous and Normally distributed
88
if normally distributed, what is true about the mean, median and mode
Mean = Median = Mode
89
if normally distributed, what is true about the mean and SD
Mean (μ) and Standard deviation (σ) are sufficient to describe a normal distribution
90
If the data distribution is normal, then the interval is what
μ ± σ contains about 68% about of the values in the population (or sample
91
what does μ ± 2σ mean
contains about 95% of the values in the population (or sample)
92
what does μ ± 3σ mean
contains about 99.7% of the values in the population (or sample)

U1 Psychology Stats 305 (21 decks)

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