Midterm 2 Key Words

Question 1

Acceptance intervals

Answer 1

An interval which sample mean has high probability of occurring given that we know mean and variance

Question 2

Simple Random sample

Answer 2

Sample of “n” objects from population which each member has same probability of being selected

Question 3

Sample distribution

Answer 3

Probability of distribution of sample means obtained from all possible samples of same number drawn from population

Question 4

Sampling distribution of sample mean

Answer 4

Population mean

Question 5

Standard normal distribution for sample mean

Answer 5

When sample distribution of sample mean is Normal distribution, standard normal RV Z can be computed

Question 6

Finite population correction factor

Answer 6

Used to adjust variance estimate for estimates mean (N-n) / (N-1)

Question 7

Central limit theorem

Answer 7

As sample becomes larger, CLT states the distribution becomes a normal distribution (bell curve)

Question 8

Law of large numbers

Answer 8

Sample mean will approach population mean as “n” becomes larger

Question 9

Sample proportions

Answer 9

Proportion of individuals in sample with certain characteristics or trait

Question 10

Sampling distribution of sample proportions

Answer 10

For large samples the sample proportions is normally distributed with mean P

Question 11

Chi-square distribution

Answer 11

Provides link between sample and population variances

Question 12

Expected value

Answer 12

Average of blues taken as number of replications increases

Question 13

Mean of X

Answer 13

Expected value of X

Question 14

Standard deviation

Answer 14

Measure of how dispersed data is in relation to mean

Question 15

Variance

Answer 15

Measure of dispersion that takes into account spread of all data points

Question 16

Probability density function of normal distribution

Answer 16

Used to define random variables probability coming within distinct range of values

Question 17

Probability density function

Answer 17

Relationship between RV and it’s probability

Question 18

Properties of normal distribution

Answer 18

1. Mean is expected value
2. Shape of pdf is symmetric bell curve

Question 19

Uniform probability distribution

Answer 19

All outcomes are equally likely

Question 20

Cumulative distribution function (CDF) of normal distribution

Answer 20

Area under normal pdf to the left of given value x

Question 21

Range probabilities for normal RV

Answer 21

Probability of area under corresponding pdf between a and b

Question 22

Standard normal distributions

Answer 22

Normal distribution with mean = 0 (centered at 0) and SD = 0

Question 23

Exponential probability distribution

Answer 23

Continuous distribution that concerns the amount of time until specific event happens

Question 24

Joint cumulative distribution F(x1, x2, …)

Answer 24

Defines probability that X1 < x1, X2 < x2 and so on

Question 25

Marginal distribution

Answer 25

Distribution of single or multi variables in a multivariate distribution

Question 26

Sums of random variables

Answer 26

Mean of their sum is the sum of their means

Question 27

Covariance

Answer 27

Measure between 2 random variables and to what extent they change together

Question 28

Correlation

Answer 28

Extent which 2 variables are linearly related

Question 29

Difference between pair of random variables

Answer 29

Mean of difference= difference between both means
Variance of difference (if cov = 0) = addition of both variance