Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Applied Statistics - Psychology > Test One - Chapters 1-6 > Flashcards

Test One - Chapters 1-6 Flashcards

1
Q

Variability

A

The degree to which scores in a distribution are spread out

How much distance to expect between one score and another

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

Standard Deviation

A

The distance between each score and the mean
The average distance from the mean

Most commonly used measure of variability

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

Standard Deviation for Samples

A

Samples are consistently less variable than their population
Sample variability is a biased estimate of population variability
Consistently underestimates the population value

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

Descriptive Statistics

A

Organizes and summarizes info from a research study

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

Inferential Statistics

A

Determines what conclusions can be drawn from a research study
- use the sample data as the basis for answering questions about the population
> to accomplish this, typically built around the concept of probability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Statistics

A

A set of mathematical procedures for organizing, summarizing and interpreting info

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

Parameter

A

A value that describes a population

i.e. 65% are female

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Statistic

A

A value that describes a sample

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

Sampling Error

A

Discrepancy between the sample and the population

Unpredictable, random differences that exist between samples

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

Operational Definition

A

A statement of procedures (operations) used to define research variables

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

Discrete Variable

A

Variable with separate, indivisible categories

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

Continuous Variable

A

Infinite number of value between two observed values

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

Deviation Score

A

x-u

u= mew

Sum of deviation scores should always be 0

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

Nominal Scale

A

classify individuals into categories that have different names
eg. gender, university, etc.

direction of difference = no
magnitude of difference = no

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

Ordinal Scale

A

set of categories organised in an ordered sequence
eg. t-shirt size, ranked place in a race, class, etc.

direction of difference = yes
magnitude of difference = no

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Interval Scale

A

categories form a series of intervals all of the exact same size
eg. temperature or golf scores

  • arbitrary zero point -> zero represents the presence of something
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Ratio Scale

A

categories form a series of intervals all of the exact same size
eg. distance, time, weight

  • absolute zero point -> zero represents the absence
18
Q

N v.s. n

A 
N = total number of scores in a population
n = total number of scores in a sample
19
Q

u (mew) v.s. M

A

u (mew) = mean of a population
i.e. Σx/N

M = mean of a sample
i.e Σx/n

20
Q

Order of Operations

A

(1) parentheses (_____)
(2) squaring
(3) x or /
(4) Σ
(5) +/-

21
Q

Central Tendency

A

single value that defines the average score
identifies the center of the distribution

no single measure will always produce a central, representative value in every situation

uses mean, median and mode to find “center”

22
Q

Weighted Mean

A

combining two sets of scores to find the overall mean

*below the 1 and 2 represent the set

Σx1 + Σx2 / n1 + n2

23
Q

Rules of the Mean

A

changing the value of any score will change the mean

24
Q

Bimodal or Multimodal

A

two or more modes

25
Q

The Mode is preferred when…

A

nominal scale of measurement
discrete variables
describing the shape of the distribution graph

26
Q

The Mean is preferred when…

A

preferred measure of central tendency

27
Q

The Median is preferred when…

A

few extreme scores
unknown or undetermined scores
no upper or lower limit for one category

28
Q

Variability

A

the degree to which scores in a distribution are spread out

how much distance to expect between one score and another

29
Q

Standard Deviation

A

most commonly used measure of variability

the distance between each score and the mean
the average distance from the mean

30
Q

σ v.s. s

A 
σ = standard deviation for a population
s = standard deviation for a sample
31
Q

σ²

A

variance

= SS/N

32
Q

Computational Formula

A

SS = ΣX2 - (ΣX)2/N

33
Q

Standard Deviation for Samples

A

samples are consistently less variable than their population
sample variability is a biased estimate of population variability
consistently underestimates the population value

to correct for this do n-1
i.e. 
sample variance is: 
s2 = SS/n-1
sample standard deviation is: 
s = square root of SS/n-1
34
Q

z-Scores

A
  • statistical technique that uses the mean and standard deviation to transform each x-value into a standardized score
  • tells us exactly where x-values are located in a distribution
  • sign tells whether the score is above (+) or below (–) the mean
  • number tells distance (number of standard deviations) from the mean
35
Q

Characteristics of a z-score distribution

A
  • shape of z-score distribution will be the same as the original
  • each individual score stays in the same position
  • the mean is always = 0
  • the standard deviation is always = 1
36
Q

Probability

A

For a situation in which several different outcomes are possible, the probability for any specific outcome is defined as a fraction or a proportion of all the possible outcomes. If the possible outcomes are identified as A, B, C, D, and so on, then:
probability of A =
number of outcomes classified as A / total number of possible outcomes
- probability gives us a connection between populations and samples

37
Q

The role of probability in inferential statistics

A

Probability is used to predict what kind of samples are likely to be obtained from a population.

Probability establishes a connection between samples and populations. Inferential statistics rely on this connection when they use sample data as the basis for making conclusions about populations.

38
Q

Simple Random Sample

A

A simple random sample requires that each individual in the population has an equal chance of being selected.

39
Q

Random Sampling

A

• each individual in the population has an equal chance of being selected for a sample.
p = 1/N
• the probabilities must stay constant from one selection to the next if more than one person is selected
- sampling with replacement

A sample produced by this technique is known as a random sample.

40
Q

Probability and Normal Distribution

A
  • highest frequencies are in the middle (close to the mean)

* lowest frequencies are in the tails (highest and lowest scores)

41
Q

Probability and z-Score Distribution

A
  • percent of scores that fall within each region

* regions on left side of 0 are the same as the right side (symmetrical)

Applied Statistics - Psychology (3 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions