ch.1-3

Question 1

Parameter

Answer 1

a numerical measurement describing some characteristic of a population

Question 2

Statistic

Answer 2

a numerical measurement describing some characteristic of a sample

Question 3

Continuous

Answer 3

result from infinitely many possible quantitative value, where the collection of values is not countable such as lengths from 0cm to 12 cm

Question 4

Discrete

Answer 4

result when data values are quantitative and the number of values is finite or countable such as the number of tosses of a coin before getting tails or categories and can’t be arranged in any ordering scheme

Question 5

Nominal level of measurement

Answer 5

data that consists of names, labels

Question 6

Ordinal level of measurement

Answer 6

if data can be arranged in some order but differences between data values either can’t be determined or are meaningless. ex) course grades and ranks

Question 7

Interval level of measurement

Answer 7

if data can be arranged in order and the differences between data values can be found and are meaningful. Data at this level don’t have a natural zero starting point at which none of the quantity is present. ex) temperatures and years

Question 8

Ratio level of measurement

Answer 8

data can be arranged in order, differences can be found and are meaningful, and there is a natural zero starting point (where zero indicates that none of the quantity is present). ex) class times

Question 9

Experimental

Answer 9

we apply some treatment and then proceed to observe its effects on the subjects; researcher can manipulate

Question 10

Observational sampling

Answer 10

researcher is not able to control (1) how subjects are assigned to groups and/or (2) which treatments each group receives.

Question 11

Simple random sample

Answer 11

a sample of n subjects is selected in such a way that every possible sample of the same size n has the same chance of being chosen

Question 12

Systematic sampling

Answer 12

select some starting point; then select every kth (such as every 50th) element in the population

Question 13

cluster sampling

Answer 13

we first divide the population area into sections or clusters and then we randomly select some of those clusters and choose all the members from those selected clusters

Question 14

Random sampling

Answer 14

each member of the population has an equal chance of being selected

Question 15

frequency versus relative frequency versus cumulative frequency

Answer 15

Frequency distribution: how data is partitioned among several categories or classes by listing the categories along with the number (frequency) of data values in each of them 
Relative frequency distributions: each class or category is replaced by relative frequency (or proportion) or a percentage. 
Cumulative frequency distribution: the frequency for each class or category is the sum of the frequencies for that class and all previous classes

Question 16

Convenience sampling

Answer 16

use results that are easy to get

Question 17

Stratified sampling

Answer 17

subdivide the population into at least 2 different subgroups or strata so that subjects within the same subgroup share the same characteristics(like gender or age) then draw a sample from each subgroup

Question 18

Midrange

Answer 18

maximum data value plus minimum data value divided by two

Question 19

Standard deviation

Answer 19

how much data values deviate from the mean

Question 20

Variance

Answer 20

measure of variation equal to the square of the standard deviation

Question 21

z score

Answer 21

number of standard deviations that a given value x is above or below the mean

Question 22

Empirical rule

Answer 22

for data sets having a distribution that is approximately bell-shaped about 68% of values fall within 1 standard deviation, 95% within 2, and 99.7% within 3

Question 23

Chebyshev’s theorem

Answer 23

whereas empirical rule only applies to bell-shaped data, this theorem applies to all data: at least ¾ of data lies within 2 standard deviations and 8/9 within 3