STATISTICAL ANALYSIS

Statistical analysis

Statistical analysis

Question #1

(a) Discrete variable

A discrete variable is a variable whose measurement unit cannot be subdivided. The integer is taken as a whole number such as 1, 2, or 3. For instance, number of siblings is a discrete variable, as the number of siblings cannot be subdivided (Healey, 2011, p.9).

(b) Continuous variable

A continuous variable is a variable that can be subdivided. The number can be taken as a decimal number also. For instance, time is an example of continuous variable that can be divided into minutes and seconds (Healey, 2011, p.9).

The variables are categorized below into discrete and continuous variables, and the level of measurement:

Variables

Continuous/ Discrete variable

Level of measurement

Gender

Discrete

Nominal

Age

Continuous

Ratio

Height

Continuous

Ratio

Temperature

Continuous

Interval

Blood Pressure

Continuous

Ratio

Employment status

Discrete

Nominal

Satisfaction rating

Discrete

Ordinal

Question #2

(a) Nominal data

The nominal data is a categorical data. The values can be assigning to the nominal data but the data is not in order (Stephens, 2009, p.5). For instance, the dominant cerebral hemisphere can be categorized by assigning values such as; 1 for the right hemisphere and 2 for the left hemisphere.

(b) Ordinal data

The ordinal data is a data that must be in order. An ordinal data is a data that can be ranked and can have a rating scale. It can be put in order but cannot be measured (Velleman & Wilkinson, 1993, p.67). For instance, the degree of pain is an ordinal data. The degree of pain can be rated from 0 to 10. The value near to 0 indicates that degree of pain is less, and value nearer to 10 indicates that degree of pain is higher. The rating must be in order as 0 to 10 rating indicates the intensity of pain.

(c) Interval or ratio data

The interval data is a data in which there is a difference between the two values and the difference is meaningful in interpreting the data (Stephens, 2009, p.5). For instance, the temperature on 1st Feb was 25 °C and on 20th March, the temperature was 50 °C, the difference between the two values of temperature shows the interval and it is interpreted that on 1st Feb, the weather was warmer than on 20th March.

The ratio data is a scalar data and values can be assigned to the ratio data. It can be arranged in an order and the differences can be arithmetically measured and interpreted. For instance, A consumes 20 gm fat per day and B consumes 40 gm fat per day. it is calculate d an interpreted that B consumes fat two times more than A that is 40/20= 2 times.

Question #3

(a) Normal distribution curve

The normal distribution curve involves the continuous quantitative data that which has a normal distribution that is the mean is zero, and equal values lies at the right side and left side of the mean point. The shape is bell curve shape. The mean is the centre point of the curve and standard deviation is the width and height of the curve. The normal curve depends on the mean and standard ...