Appendix B

Question 1

chi-square test

Answer 1

goodness of fit or contingency test. Test of significance designed to determine if the difference in observed and expected frequencies are significant within a selected degree of probability (frequency data vs continuous data)

Question 2

continuous variable

Answer 2

infinite number values possible (ex. measurement of haemoglobin in blood may be in whole grams or fractional units)

Question 3

discrete variable

Answer 3

fixed numerical values with no intermediates possible (ex. number of toes, number of trees, number of white blood cells)

Question 4

dispersion

Answer 4

scatter of values from a central point

Question 5

histogram

Answer 5

graph of a frequency distribution of a continuous variable

Question 6

interpolation

Answer 6

predicts values within range of values measured but which do not actually exist in the set

Question 7

Mean

Answer 7

denoted by X with line on top

Question 8

measurement error

Answer 8

reflects discrepancy between a measurement and the true value of the variable being measured

Question 9

median

Answer 9

middle value in an ordered set of values (half values are less than and half more than)

Question 10

mode

Answer 10

most frequently occurring value

Question 11

normal distribution

Answer 11

a theoretical frequency distribution that is bell shaped and symmetrical

Question 12

population

Answer 12

in stats, all possible values of a particular variable in all sampling units of a particular group

Question 13

precision

Answer 13

nearness of values of successive measurements of the same specimen

Question 14

range

Answer 14

largest values - smallest values

Question 15

scientific notation

Answer 15

write number as factors of powers of 10

Question 16

significant figures

Answer 16

reflects the accuracy for which we are able to measure

Question 17

standard deviation

Answer 17

a measure of the dispersion of a set of data about the mean (calculated as the square root of the variance)
- average size of the deviation from the mean

Question 18

standard error

Answer 18

a measure of how reliable the sample mean is as an approximation to the population mean (standard deviation/square root of sample size)

Question 19

student’s t-test

Answer 19

a test of significance used to determine if the mean values of two groups of data are significantly different within a selected degree of probability (are populations the same with respect to variable tested). Tests for difference between two sample means.

Question 20

test of significance

Answer 20

Statistical test designed to evaluate probability of rejecting the null hypothesis when it is true. Example if chance of rejecting null is 1% when it is in fact true, the significance level is 1% for that test.

Question 21

variability

Answer 21

range of measured values in a population

Question 22

variance

Answer 22

a measure of how much scatter there is around the mean

• calculated as the sum of the difference between each measurement and the mean divided by the sample size minus one
• average size of the squared deviations from the mean

Question 23

variation

Answer 23

members of a given population differ from each other by characteristics they possess as a result of both genetic and environmental factors affecting the organism.

Question 24

single measurement consists of

Answer 24

• unit measured
• scale factor showing relative magnitude of value
• significant figures

Question 25

units

Answer 25

1 m = 100 cm = 1000 mm = 1 x 10^-6 micrometres

Question 26

If measurement is accurate to nearest unit

Answer 26

then zeroes are included (91 000 micrometres accurate to nearest um is 5 sig figs). If it is not accurate to nearest unit 91 000 -> the zeroes are just scale factor

Question 27

when multiplying and dividing

Answer 27

results should have no more reliability than the initial value which has the least number of significant figures 3.9 x 42.15 = 1.6 x 10^2

Question 28

when adding and subtracting

Answer 28

result should contain only as many decimal places as did the initial value with the least number of decimal places 18.328 + 2.3 = 20.6

Question 29

exception to arithmetic rules applying to sig figs

Answer 29

when calculating the mean of a set of measurements, usually the mean is given one more significant figure than the measurement with the least number of significant figures

Question 30

If the digit to be rounded is followed by a five followed by zeroes...

Answer 30

- if the digit is EVEN leave it unchanged ex. 12.50 becomes 12 when rounded to 2 sig figs - if the digit is ODD increase it by one ex. 11.50 becomes 12 These theoretically cancel each other out

Question 31

sample size and pop are abbreviated by?

Answer 31

sample size = n | population = N

Question 32

Size of sample must always

Answer 32

be reported so others can assess results and their applicability. You also cannot increase sample size by endlessly repeating measurements on the same sampling unit.

Question 33

Qualitative attributes

Answer 33

Easy to group as only a definite number of possibilities. Ex. sex, hair colour, or presence of a certain disease.

Question 34

Quantitative attributes

Answer 34

Counting something, may be discrete or continuous

Question 35

tables should be designed so

Answer 35

they are read vertically not across

Question 36

bar graph is used for

Answer 36

discontinuous (discrete) variables (scale line must start at zero and bars must be wider than spaces between them)

Question 37

line graph

Answer 37

shows relationship between dependent and independent variable (time relationships)

Question 38

statistics of location

Answer 38

Describe the position of a sample along a given dimension. Will give you a representative value of the observed set. Do not represent distribution of the observations rather the measures of central tendency (mean median mode).

Question 39

statistic of variation

Answer 39

Shows variability (dispersion) of a data set. Range is often represented by variance and standard deviation or standard error

Question 40

sum

Answer 40

denoted by weird E

Question 41

assumptions of chi-squared test

Answer 41

1. data must consist of samples taken at random from a large population 2. for each sample taken there is a restricted number of outcomes that can be divided into distinct categories 3. probabilities for each outcome are independent of each other and do not

Question 42

chi-squared statistic tells us

Answer 42

whether an observed count deviates significantly from the mean. ex. (10 females and 10 males chi-squared value is 0, 20 females and 0 males is a value of 20)

Question 43

When do you use a t test vs a chi-squared test?

Answer 43

- a t test is for testing the null hypothesis that "there is no difference between the means of two samples" example number of leaves on shady plant vs sunny plant, height of girls vs boys - a chi-squared test looks at the relationship between two variables

Question 44

What are the necessary conditions of the data set for a t- test

Answer 44

Must be two variables: one is categorical and can only have 2 options and the other must be quantifiable by some mean

Question 45

What are the necessary conditions of the data set for a chi-squared test

Answer 45

Two categorical variables which can have numerous levels (presidential candidate voted for vs. ethnicity)