Descriptive statistics

Question 1

Measures of central tendency definition?

Answer 1

the relationship of the values with the central point

Question 2

Least to most precise/ sensitive MOCT

Answer 2

mode -> median -> mean

Question 3

how to calculate mean ?

Answer 3

= the average

add up all numbers/ number of numbers

Question 4

how to calculate mode?

Answer 4

= most common number, may be more than 1

putting similar scores together, and counting which appears most frequently

Question 5

median calculate?

Answer 5

= central value

- arranging scores in order and finding mid point

Question 6

advantages of the mean?

Answer 6

+ appropriate to use for further statistical analysis such as standard deviation
+ appropriate to use for ordinal, interval, ratio levels of data

Question 7

mean disadvantages?

Answer 7

• affected by extreme scores so can misrepresent no.s

- may produce a value that no ppt in the data set achieved

Question 8

mode advantages?

Answer 8

+ unaffected by extreme scores
+ can be used with nominal (categorical data) & provides info abt freq
+ unlike mean and median, there is always a modal score

Question 9

mode disadvantages?

Answer 9

• ignores values by only looking at the freq of no.s, this may lead to biased representation as an outlier score may be the most frequent
• can be unclear as data may have several modes - bimodal = 2

Question 10

median advantages?

Answer 10

+ makes use of all the values but is not as biased by extreme scores as mean
+ can be used with ordinal data

Question 11

median disadvantages?

Answer 11

• more open to bias from extreme scores than mode

- unhelpful for further statistical analysis such as standard deviation

Question 12

what is measures of dispersion?

Answer 12

how dispersed or spread out the data are

Question 13

range calculated?

Answer 13

the range is a measure the spread of a set of scores, shown by the difference between highest and lowest

Question 14

standard deviation?

Answer 14

measure of the spread of data around th mean.

higher value = more variation in your scores

Question 15

range +?

Answer 15

+ easier to calc than standard deviation

+ takes into account extreme values

Question 16

range -?

Answer 16

• affected extreme values and does not take into account the no. of observations in the data set
• it does not give info on whether the scores are clustered around the mean or spread out

Question 17

SD +?

Answer 17

+ Gives more precise and informative measure of dispersion than range, as it doesn’t just take into account highest & lowest
+ less affected by anomalous results than range - extreme scores are ignored

Question 18

SD -?

Answer 18

• more complicated to calculate then range

- can only be used when data set is normally distributed (bell shaped curve) and not skewed

Question 19

What is meant by low standard deviation?

Answer 19

Data is clustered around average

Question 20

what is meant by high standard deviation?

Answer 20

Tells us data is dispersed

Question 21

When is SD used?

Answer 21

When distribution of data is approx normal- a bell shaped curve
To tell when data is normal, expected, unusual

Question 22

What is the 68-95-99.7 rule?

Answer 22

About 68% of data falls within the 1st sigma
About 95% of the data falls within the 2nd sigma
About 99.7% of data falls into 3rd sigma

Question 23

Acting with the mean SD allows us to determine whether

Answer 23

A value is statistically sig or as a part of standard deviation (expected)