Vocabulary Ch 1 Flashcards
1
Q
Mean
A
Arithmetic average
The sum of the scores divided by the number of scores
2
Q
Median
A
Arrange numbers in order from smallest to largest
Midpoint of the list
Remember: with even numbers, we add the middle numbers
Ex: 1,1,4,5,7,8
4+5/2=9/2 or 4.5
3
Q
Mode
A
The score or category that has the greatest frequency
4
Q
Std
A
On average, how far any given data point is away from the mean
Average distance from the mean
If it is 0, then it is the exact same score, so there is no variation
- M=80 so our s= 4, what does it mean? 4 pts away from the mean
5
Q
Statistically significant
A
The results are not likely not due to chance
Ex: cheerleaders and pizza
Non cheer:3.4
Cheer:1.5
6
Q
For what type of data, would you typically use the mode?
A
Nominal data
7
Q
When we use the median instead of the mean:
A
Huge # for sample we use the ______ instead of the mean
8
Q
Pie chart
A
Hard to compare sections
We avoid them
9
Q
Study
A
- observe/ assess without changing the environment
- correlational studies
10
Q
Experiments
A
- manipulates variables while observing them, then examines how changes in one/ more variables affect changes in others
- cause and effect
11
Q
Mode
A
Describes the Ideal form of central tendency measurement for nominal, it is the______
12
Q
Median
A
Describes the ideal form of central tendecy for ordinal, it is the ______.
13
Q
Mean
A
Describes the ideal form of central tendency measurement for interval, it is the ____.
14
Q
Standard deviation
A
On average, how far any given data point is away from the mean.
Measure of how spread out data is
If it is 0, then it is the exact same score for everything, no variation.
15
Q
Stats
A
Collecting, analyze, and understanding data Goal: effective decision making Bring life to a data table Turn ugly data into a beautiful princess Gain insight Find solutions
16
Q
Outliers
A
Data points away from the others
17
Q
Qualitive research
A
Quality Words Observed but not readily measured Smells, colors, appearance, beauty, etc. Friendly demeanor, positive outlook, considerate, etc. Interview style
18
Q
Quantative research
A
"Quantity" #'s Data easy to quantify Data Can be measured Height, weight, age, income Ex: 57 males, 63 females 47% on deans list Transfer rate 72%
19
Q
Descriptive stats
A
Summary of info regarding one variable
Ex: mean, median, mode, etc
Small part of stats
20
Q
Inferential stats
A
"We have a sample, let's see how we can relate it to the population" "Want to infer an unknown quantity" Big part of stats Ex: sample of elac students Sample to population
21
Q
Primary data
A
Data you gather yourself
Pro:
-phrase it yourself
Design questionnaire
22
Q
Secondary data
A
Secondary analysis Gather from someone else Pro: -set for you, so you just analyze it -No bias b/c it is a big population Con: - you can get stuck with how it is phrased
23
Q
Cross sectional data
A
Do it all at the same time w/ diff groups More pratical, can get data collection done Ex: remember class demonstration with marriage
24
Q
Longitudinal data
A
Same group, but follow over time
Stronger design overall b/c work with same people
25
Operationalize
How you measure concepts
26
reliability
Consistency of mesurement
Consistency
Ex: watch and time
27
Validity
Accuracy
To have validity, you have reliability
Stronger than realibility
"Consistency plus getting the right answer"
Stronger
Ex: watch is always consistent with time but may not be valid
Weigh self: says you're 186 when you are really 190
Consistent but not valid
28
Interrator realibility
Used to assess the degree towhich different raters/ observers give consistent estimates of the same phenomenon
29
Type 1 error
```
Alpha
False positive
Rejecting a true null hypothesis
Ex: pregnancy test tells you pg but arent
Replicate study to prevent it
```
30
Type 2 error
```
Beta
False negative
Accepting a false null hypothesis
Ex: tells you you arent pregnant, but are
Increase sample size
```
31
Nominal
Weakest
Categories only, no ordering to it
One is not higher or better than the other
Ex: county you live in, car you drive,hair color
Categorical data-race
32
Ordinal
```
In between
Has direction, can be ranked, but not precise
Ex: size of coffee cups: S M L
Tshirt size- S M L
Grades: A, B, C
Likert scales
Order but no precision
```
33
Interval
Ratio
Strongest
Has directiom and precision
Increases or decreases at equal intervals
Ex: height, age, weight, income, weight, collar size from neck of a shirt
Like a real #: how old you are, weight, etc.
Ratio is subtype but interval and ratio are the same thing
Inches/ units are size of weight
Gpa
34
Likert scales
Most items will be closed ended( multiple choice)
1-5(ordinal)
Avoid neutral response
Ex: we should leave Iraq
Strongly agree, disagree, agree, strongly agree
Common to close the questionnaire with an open ended question
Include demographic background variables( age, gender, etc)
Do bckground items near end after main component of questionnaire
Survey must be voluntary
Info is confidential
35
Multiple regression
Interval
| Understand relationship between one dependent variable and several independent variables
36
Likert scales
```
Ordinal data
1-4 standard scale but can be higher
Ex: pizza
1. 2 3 4
Sd. D A Sa
Want it low to high
Higher #: more agreement
Low #: less agreement
Dont do 10 pt scale b/c lose reliability and validity
```
37
Anonymity
Dk at all who it is
38
Confidentiality
Know who it isbut wont tell who it is
Anonymity is stronger than __________.
39
Response rate
How fast people reply to the survey
Good when it is 90%
@ least get over 50%
40
Sampling
Elac students 42,000
41
Census
Everyone in the population that you're studying
42
Random sampling
Preferred
Randomly pick name, #, etc.
Everyone has an equal chance to be picked
This form of sampling is preferred
43
Sample B
Which sample is better?
A. Maine: population is 1.3 million
B. USA: population is 325 million
It is ___ b/c it has a larger sample and has more room for random sampling.
Better sample size
44
Independent variable
```
Presumed cause
Ex: test score and fruit
Fruit is the ___________ ________.
Predictor variables
Tv watching and hours study with gpa
The ___________ ________ is the hours study.
```
45
Dependent variable
Effect/ outcome
Test score is __________ ________
Tv watching and weight: the weight is the __________ _______
Hours study and gpa: gpa is ________ ________
46
Theory
Confirmed hypothesis
Ex: theory of evolution
47
Hypothesis
Educated guess
You test your theory
A testable prediction
48
Example of independent variable
Drinking niagra water vs dasani before a test and seeing which score is better
The drinking water for dasani vs niagra is the ___________ ________.
Have multiple available for your research
49
Dependent variable
Drinking dasani vs niagra water before a test and seeing which score is better.
The test score that is better as a result of the drinking water brand is the _______ ________.
50
Hypothesis
```
"If i do this, then this will happen"
Ex: oj outperform those who drink water on a test
Students who sleep 7 hours do better in class than those who sleep less
```
51
5 step critical thinking strategy
1. Identify the claim and assume it's false
2. Evaluate the supporting evidence considering assumptions nd methodology.
Ex: class demonstration of 10 ppl with gum
3. Consider alternative explanantions.
Ex: haunted building, but look at other reasons to explain why it isn't haunted such as, hearing a noise in the building but it could be the wind.
4. Seek additional evidence for/ against alternative explanations-> look at other evidence not just your own reasoning.
5. Based on all the evidence, make a conclusion. True/ false evidence
52
Relative frequency
Population is large, so you can use a graph to represent large populations
Ex: bluegill and bass to show diff. In amount
53
Smooth curves
```
Normal curves
Not jagged
Interval data/ ration data
Normal distribution
Bell shaped
In a perfect curve, median, mode, and mean are the same
```
54
Shape of smooth curve
Symmetrical
| Bell shaped
55
Shape of smooth curve
Skewed
Leaves a tail
Positive( right skewed)
Negative( skewed left)
56
Dependent variable
Measures whether it changed an experiment or not
57
Elements of an experiment
1. Random assignment
2. Independent variable
3. Dependent variable
4. Experimental condition
5. control condition
58
Experimental condition
Receive experimental tx
59
Control condition
Individuals dont receive the experimental tx
No tx/ receive a neutral placebo tx
Provides a baseline for comparison with the experimental condition.
60
B.
Which is better?
A. Bob is studying "work ethic" sample of 2,000 students
Non random sampling of night students taking psych classes
B. Johnny motivation levels, sample size of 500 students, random sample of all elac students
Sample _ is better b/c we have a better size for sampling and it is random.
61
Central tendency
1. Mean
2. Median
3. Mode
62
Variation
Range
| Std
63
Variance
Average squared distance from the mean
64
Sum of squares
SS
| The sum of the squared deviation scores
65
Central tendency
Statistical measure to determine a single score that defines the center of the distribution
Goal: find the single score that is the most typical or most representative of the entire group.
Attempts to identify the average
66
Variability
Provides a quantatitive measure of the differences between scores in a distribution nd describes the degree to which the scores are spread out or clustered rogether.
Purpose is to obtain an objective measure of how the scores are spread out in a distribution.
Tells if scores are clustered together or are spread out over a large distance
Distance of a score or how much distance to expect
Measures how an individual score reps the entire distribution
Provides how much error to expect if youre using a sample to rep a population
67
Deviation
Distance from the mean
68
Z scores
How many stds a person is below/above the mean
Purpose: identify and describe the exact location of each score in a distribution.
z= +1.00 1 std above the mean
Z=2.00 2 stds above mean
Z= 0.50 located above the mean by exactly 1/2 std.
Z= x-m/std
69
Raw score
Original unchanged scores that are the direct result of measurement
Described as X for ex: X=83
70
Ordinal
Likert scale is ________.
71
Interval
Gpa is _________.
72
Ordinal
Letter grades are _______.
73
Ordinal
Tshirts size is _________.
74
Interval
Age is _________.
75
Nominal
County of residence is ________.
76
Discrete variable
```
Countable #
# of people in a stats class
People/ things classified into different categories i.e. Male/ female
```
77
Continous variable
Stopped at any point/ time
Measuring time in hours, minutes, seconds or fraction of seconds
Divided into an infinite number of fractional parts
78
Secondary data
Which is oreferred, primary ir secondary data collection, and why?
____________ data is better b/c we analyze the info that is set for us, there is no bias, and we can go from there.
