week 1 - 5 RM1 data concepts

Use of histograms  

• Organise score in intervals  

• Can look different due inerval with  

• Mid interval value (in centre of interval)

Unimodal

one peak, (not necessarily in the centre of the distribution) 

Bimodal

two peak

Postive skewed (tail)

negative skewed

parameters

measure on a whole population of objects. Inferential stats used to draw conclusion about a whole population  

3 thinsg that determine data analysis

1. Type of data  

2. Number of group or variable  

3. Diffeences versus relationships (difference between x and y OR relationship between X and Y)  

Nominal

• Used for purpose of classification  

• Eg: 1 = male, 2 = female OR jersey numbers of football players  

• Categorical data often measures using nominal scale  

Ordinal

• Order along a continium  

• Eg: rankings 

• Higher or lower score can indicate something  

 

Interval Scale

• Interval between scale points  

• Eg. Fahrenheit scale: 90 F and 80F, pain sensitivity 

• Not always use to maek infrences about ratios 

• Equal intervals represent equal things 

 

Ration Scale

• Has a true zero point, which corresponds to absence of thing being measured  

• Eg: 0 Celcius is NOT a true zero, 0 seconds IS a true zero  

• Can allow use to use phrases such as “half as much”  

LQ formula

(N+1) x 1/ 4  

UQ formula

(N+1) x 3/ 4 

Z score formula

z = X - mew/SD

Mean Median mode in norm distribution..

are the same

Within 1 SD of score is how many %?

68.3%

Within 2 SD of score is how many %?

95.4%

Within # SD of score is how many %

99.7%

SD of sampling distribution formula

population SD/root over N