問題一覧
1
To compute for the mean of a discrete random variable, follow these steps: 1. Construct the __________ 2. Determine the value of ______ 3. Add all the values of ______ to determine Σ[X•p(x)]
Probability distribution, X•p(x), X•p(x)
2
The ______ of a set of numbers measures how far apart the set of elements are spread out
Variance
3
Variance is always _________
Nonnegative
4
The ______ of a discrete random variable describes the dispersion or the variability of the probability distribution
Variance
5
A ________ indicates that the data points tend to be very close to the mean and to each other
Small variance
6
A _______ indicates that the data points are very spread out around the mean and from each other
High variance
7
A _________ indicates less variability
Smaller stdv
8
A _____________ indicates greater spread/variability
Larger stdv
9
A _______ means greater consistency or reliability in performance or outcomes
Lower stdv
10
A variance of ____ indicates that all the values are _____
Zero, Identical
11
Steps in computing the variance and stdv: 1. Compute for the _____ of the probability distribution 2. Construct the column ______ 3. Find the _____ and ____ using their corresponding formulas
Mean, X²•p(x), Variance, Stdv
12
3 types of distribution
Positive skew, Symmetrical distribution, Negative skew
13
?
Positive skew
14
?
Symmetrical distribution
15
?
Negative skew
16
In positive skew, the mean is ______ than the mode, and tail is longer on the _______
Greater, Right
17
In negative skew, the mode is _____ than the mean, and the tail is longer on the _____
Lesser, Left
18
A distribution which most of the scores tend to be closer to the mean
Normal distribution
19
The random variable of normal distribution is called the __________
Normal random variable
20
Normal random variable
Continuous random variable
21
Normal distribution
Continuous probability distribution
22
A graph that represents a normal distribution
Normal curve
23
Mu
Mean
24
Sigma (lowercase)
Stdv
25
Pi
3.14159
26
Euler's constant
2.71828
27
The term _______ refers to the fact that this kind of distribution occurs in many different kinds of common measurements
Normal
28
This distribution is the commonly used distribution in probability theory and statistics
Normal distribution
29
The most common example of a normal distribution
Standard normal distribution
30
In standard normal distribution, the mean is __ and the stdv is __
0, 1
31
The _____ of a normal distribution is always in the center of the normal curve
Mean
32
The stdv determines the _______ of the distribution
Spreadness
33
These two are used to determine the percentage of scores that lie in a given area of the distribution
Mean, Stdv
34
Interpretation above the mean
Mean+1stdv, Mean+2stdv, Mean+3stdv
35
Interpretation below the mean
Mean-1stdv, Mean-2stdv, Mean-3stdv
36
A continuous probability distribution where most of the scores tend to be closer to the mean
Normal distribution
37
A continuous random variable of a normal distribution
Normal random variable
38
A normal distribution is _______ about its mean
Symmetric
39
The _____, ______, and _______ of a normal distribution are all equal
Mean, Median, Mode
40
A normal distribution is ____ at the center and _______ at the tails
Thicker, Less thicker
41
Thicker on the center
More scores
42
Less thick on the tails
Fewer scores
43
Approximately _____ of the area of a normal distribution is within 1stdv of the mean
68.26%
44
Approximately _____ of the area of a normal distribution is within 2stdv of the mean
95.44%
45
Approximately _____ of the area of a normal distribution is within 3stdv of the mean
99.74%
46
States that 68.26% of the scores fall within 1stdv away from the mean, 95.44% of the scores fall within 2stdv away from the mean, and 99.74% of the scores fall within 3stdv away from the mean
Empirical rule
47
Scores that are more than 2 stdv away from the mean
Outliers
48
Scores that are more than 3stdv away from the mean
Extreme outliers