Types of Measurement Scale, Variables and Hypothesis

Types of Measurement Scale:

1. Nominal Scale:

• Classification only.

• Mode can be calculated only.

• Like Gender, Cold drink options.

2. Ordinal Scale:

• Classification + Order.

• Median, Mode can be calculated.

• Like social class (Upper, middle, lower).

3. Interval Scale:

• Classification + Order + Distance.

• Mean, Median, Mode and standard deviation all can be calculated.

• Like Temperature.

4. Ratio Scale:

• Classification + Order + Distance + Absolute Origin

• Mean, Median, Mode and standard deviation all can be calculated.

• like age, income, height, weight, size.

♦ Statistically Ratio Scale  is a Powerful Scale.

Characteristics of Good Measurement:

1. Reliability:

• Consistency of measurement ; meant that if you measure a variable many times so the answer should be same or nearer at all the time. A measure is dependable to the extent that is supplies predictable outcomes.

2. Validity: 

• Is the instrument is measuring the same characteristics which you are intending and supposed to measure.

3. Economy: 

• In minimum rate/amount/price you get the good measurement.

Relationship between Reliability And Validity:

• If an instrument is reliable it may or may not be valid.

• If an instrument is not reliable it can never be valid.

• If an instrument is valid it should be reliable.

• If an instrument is not valid it may or may not be reliable.

• Reliability is necessary condition.

 Validity is sufficient condition.

Types of variables:

Variable:

•Generally, it is a characteristics.

Any thing which is changed from time to time, place to place, situation to situation is called variable.

1. Continuous Variables:

 • Variables which are measureable with the help of instrument.

• In points, Fraction.

• Like height, weight, etc.

2. Discrete Variables:

• Variable which are countable.

• In whole nos.

• Like, chair in room, Fans in room etc.

3. Dependant Variables (DV) :

• Estimated the impact of IV on DV.

4. Independent Variables (IV) :

• Manipulation on variations did by ownself.

5. Moderating Variable (MV) :

A Moderating Variable is one that strengthens or weakens the relationship between IV and DV. A Moderating Variable tells us when does the chance occur and for the change occurs.

Situation:

A Manager found that off the job classroom Training positively effect employees performance but only those employee who are less then so years of age.

6. Mediating (Intervening) Variable (MIV):

A mediating variable is one that explains the mechanism of change from IV to DV. A mediating variable tells us why does the change occurs.

Situation:

Advertising efforts increase sales because increase advertising efforts first increases consumer motivation to purchase, which ultimately results in increased sales.

Situation: 

Failure to follow accounting principles creates confusion which creates problems for the company. But those companies having good experience in book keeping may revert the situation.

Types of Hypothesis:

Hypothesis:

A proposition which is ready for testing is called hypothesis.

e.g:

     Pakistan per Capita is less than 996$.

IV variable is manipulated by the researcher and the manipulation causes an effect on the DV.

DV variable is measured, predicted or otherwise monitored and is excepted to be affected be manipulation of an IV.

1. Null Hypothesis:

• A testable hypothesis.

• Always in the form of equality.

• Null Hypothesis; μ = 30 , μ ≥ 30 , μ ≤ 30

2. Alternative Hypothesis:

• A hypothesis against of which null hypothesis are test.

• Alternative Hypothesis; μ ≠ 30 , μ > 30 , μ < 30

♦ From null and alternate hypothesis ; one hypothesis should have to be true.

♦ Null and alternate hypothesis are mutually exclusive and collectively exhaustive.

Mutually Exclusive:

When the occurrence of an event/outcome prevents the occurrence of an other outcomes/events then these two events/outcomes are said to be mutually exclusive.

e.g;

If coins were tossed then the occurrence of head prevents the occurrence of tail then of is said to be mutually exclusive.

Collectively Exhaustive:

Null Hypothesis should have an equality sign, it is union to universal set.

• (= , ≥ , ≤ , ≠)

• Null hypothesis ; μ ≥ 30 

Alternative Hypothesis ; μ > 30

 ( These both hypothesis are not mutually exclusive because result can be different or change).

• Null Hypothesis ; μ > 30 

Alternative Hypothesis ; μ < 30 

( They are not collectively exhaustive because there is no equal sign and result can also be different or change).