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