Module 1/2: Lecture Notes Flashcards

1
Q

Parameters

A

A population parameter is a numerical value that describes a characteristic of a population. For example, the population mean height of all students in a school is a population parameter.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Statistics

A

Numerical description of a sample characteristic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What is the difference between a parameter and a statistic?

A

The difference between a parameter vs a statistic is that a parameter is a fixed measure describing the whole population, while a statistic is a characteristic of a sample, a portion of the target population.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Descriptive statistics (3)

What it is+ what it does+ ex

A
  • The organization, summarization and display of data
  • simplifies data to make large groups of numbers easier to grasp
  • Ex: Did you go away for break? -> ask everyone and find the amount that stayed and went away. -> use % to summarize
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Inferential statistics (3)

What it does+ generalize+ draw conclusion

A
  • Draw conclusions about a population based on data from a sample
  • Generalize about a characteristic we cannot measure directly
  • Enable researchers to draw conclusions when it might be impossible to measure all members of the population of interest
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Discrete data is

A

categorical

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Quantitative Data (2)

What it is+how is it presented?

A
  • Information about quantities; How much or how many of something
  • Presented as a set of numbers
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Continous Data

A

Take on any value in some interval and are not restricted to any list of values value in some interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Discrete data

A

Can be listed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What level of measurement is continous?

A

Ratio, Interval

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Which level of measurement can quantify the difference between values?

A

Interval, Ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Which level of measurement can add/subtract?

A

interval/ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Which level of measurement can multiply/divide?

A

ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Which level of measurement has inherent true values?

A

ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Variables(3)

What it is+ can be…

A
  • Something that varies
  • Can be a few levels (ex: 2-4 for categorical, left or right handed)
  • Can have many values (Continous data)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Experimental Study (2)

What it is+ what researchers do

A
  • A treatment, proedure or program is intentionally introduced and a result or outcome is observed
  • Researchers compares outcomes between those who received treatment and those who did not
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Independent variable

A

Actively manipulated

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Dependent Variable

A

Changes as a result of manipulation of IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Confounding variables

What it is+ varies with + impossible to…

A
  • Anything that could cause change in B that is not A
  • varies with the IV
  • Impossible to identify the cause of any change in the DV
20
Q

Validity

A

Does the experiment measure what it is intended to measure

21
Q

Reliability

A

refers to how consistently a method measures something

22
Q

Frequency Tables

A

Shows discrete data values along with frequency of each

23
Q

Unimodal

A

One highest frequency or value

24
Q

Skewed distributions

A

Have many more scores on one side of a distribution than on the other side

25
Negative skew
Left tail is longer
26
Positive skew
Right tail is longer
27
Way to measure central tendency (3)
Mean Mode Median
28
Mean
A set of scores is the sum of the scores divided by the number of scores
29
Median
The midpoint
30
Mode
The value that occurs the most often. It also represents the highest peak or column in a graphed frequency distribution.
31
Central tendacy of positive skew
32
Central Tendency of Negative Skew
33
Population mean
34
Sample Mean
35
Deviation
The distance of a score x from the mean of the distribution it is included in
36
Deviation of the entire population
(x-μ) distance between data point x and the population mean
37
Deviation of sample
(x-X̄) distance between a point x and the sample mean x-bar
38
Why do we square deviance rather then absolute it?
Because you dont want to underplay any outliers
39
When a sample variance is calculated, the sum of the values is divided by n-1 instead of n. This is done to -----
correct for the tendency of the sample variance to slightly underestimate the population variance
40
Population standard deviation symbol
σ sigma
41
Sample standard deviation symbol
s
42
What is standard deviation?
It is a measure of the variability within a distribution
43
A data point that is several standard deviation from the mean may be ....
just due to random variation but it could also signify an unsual event that needs to be investigated
44
What do Z scores do?
Gives the distance in standard deviations from a data point to the mean of the distribution it is included in
45
How are Z scores calculated?
46
Multiplying the z-score by the standard deviation tells us----- adding that to the mean gives-----
- how far the raw data value is from the mean in terms of the original data values - the exact location or data point
47
Qualitative data | Presented as
presented as names or categories