intro to stats

Question 1

what is statistics?

Answer 1

The science of Collecting,Organising ,Presenting,Analysing and interpreting data

Question 2

data

Answer 2

Data refers to set of values for a variable

Question 3

variable

Answer 3

A variable is any measured characteristic that differs for different subjects

Question 4

types of variables

Answer 4

categorical and numerical/quantitative

Question 5

Levels of Measurement- NOIR

Answer 5

categorical: Nominal Data/ Ordinal Data
numerical: interval data/ ratio data

Question 6

Nominal Data(categorical)

Answer 6

Naming/Labelling variables without any quantitative value. i.e. gender

Question 7

Ordinal Data(categorical)

Answer 7

Ranked data/ Typically measure non-numeric concepts e.g. satisfaction ratings

Question 8

Interval Data(numerical)

Answer 8

we know the order and also the differences between the values.ie. temperature/ can add or subtract

Question 9

Ratio Data(numerical)

Answer 9

Tell us about the order, the difference in value between units and have an absolute zero.i.e. weight, income

Question 10

population

Answer 10

All items or individuals about which you want to
reach conclusions

Question 11

sample

Answer 11

A portion of the population selected for analysis

Question 12

Why use a sample?

Answer 12

less costly/ less time consuming/ more practical

Question 13

two types of statistics

Answer 13

descriptive/ inferential

Question 14

Descriptive Statistics

Answer 14

Used to summarise the main aspects of your dataset using Tables, graphs, simple formulae

Question 15

Inferential Statistics

Answer 15

Methods that use data collected from a sample (small group) to reach conclusions or make predictions or inferences about the population (larger group)

Question 16

two general classes of descriptive statistics

Answer 16

Measures of central tendency/ Measures of variation/dispersion

Question 17

Central Tendency

Answer 17

Central tendency refers to the tendency data has to cluster around the centre point.i.e the average

Question 18

The three main measures of central tendency

Answer 18

mean/ median/ mode

Question 19

The Fulcrum Conceptualization

Answer 19

the mean might be considered the balancing point or turning point of a lever where the distance from the mean is equal on each side
i.e. The mean is a good central point

Question 20

mean and central tendency

Answer 20

Mean is a poor measure of central tendency for this set of data (due to outliers)

Question 21

median

Answer 21

The median represents the middle score in a dataset

Question 22

Calculating the median if even number

Answer 22

find the average of middle two ranked values

Question 23

the mode

Answer 23

he value that appears most frequently in the dataset

Question 24

nomindal data and measures of central tendency

Answer 24

Nominal data – you can only use the mode

Question 25

ordinal data and measures of central tendency

Answer 25

Ordinal data – you can use the mode or the median

Question 26

both interval and and ratio data/ and measures of central tendency

Answer 26

Interval data and Ratio data – you can use mean, median or mode

Question 27

measures of variation

Answer 27

The Range/ The Interquartile Range/ The Standard Deviation

Question 28

the range

Answer 28

Range = Max Value – Min Value

Question 29

what do Measures of variation tell us?

Answer 29

Measures of variation tell us about how scores are dispersed (distributed) around the central/average score

Question 30

the variance

Answer 30

sum of squares

Question 31

standard deviation

Answer 31

The standard deviation tells us how much, on average, scores in the dataset deviate from the mean

Question 32

variability

Answer 32

describes the distribution of scores

Question 33

Skewness

Answer 33

when data is not symmetrically distributed

Question 34

Kurtosis

Answer 34

refers to the steepness/shallowness of the distribution

Question 35

how does a small SD describe the distribution of scores ?

Answer 35

most scores cluster closely around the mean score

Question 36

how does a big SD describe the distribution of scores ?

Answer 36

most scores are spread out a lot from the mean score

Question 37

postive skew

Answer 37

more scores to the left of the peak

Question 38

negative skew

Answer 38

more scores to the right of the peak

Question 39

what presence of skewness is a problem?

Answer 39

value greater than +2 or – 2 is a problem

Question 40

Leptokurtic

Answer 40

steep curve

Question 41

Mesokurtic

Answer 41

normal curve