data analysis 10

8/9/2019 Data Analysis 10

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Applications of Data

Analysis Techniques


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Data Analysis

1) Why ?

2) How ?

3) Some important considerations before

analysis ------

a) Type of data

b) Objectives

c) Hypotheses


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Consideration 1

Types of Data ( Scales )

a) Nominal

b) Ordinal

c) Interval

d) Ratio


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Consideration 2

Objectives

What are we trying to find out ?

In order to achieve this, what kind ofinformation is required ?

Which tools are giving this information ?


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Consideration 3

Hypotheses

What is the type of hypotheses framed ?

What is the level of significance set ?

What type is the available data ?

Which technique will meet the research needskeeping the type of data in mind ?


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Descriptive Analysis

I) Measures of Central Tendency---Mean, Median, Mode

II) Measures of Variability/Dispersion---Range, Average deviation, Quartile

deviation, Standard deviation

III) Measures of Correlation---

IV) Normal distribution---


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Inferential Statistics

Types of Inferential Statistics

PARAMETRICNON

PARAMETRIC


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Parametric Statistics

Essential conditions of usage -----

1) The data is in the interval or ratio scale.

2) Both the groups have equal variance.

3) The trait/variable is normally distributed.

4) The sample is randomized.


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Non-parametric Statistics

No such conditions as parametric statistics.But when the data is ---

1) in either nominal or ordinal scale ,

2) small in size ,

3) not randomly selected ,4) homogeneity of variance cannot be

established &

5) variable is not normally distributed in the

population ( skewed )

Researcher should go for non-parametricstatistics.


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Certain Terms defined ---

1) Levels of Significance

2) Degrees of Freedom

3) Critical Value

4) Tails of a Test

5) Area of Rejection


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Testing of Hypotheses

If the calculated value of a given statistic is lesserthan the table value of that statistic, then thehypothesis is RETAINED.

If the calculated value of a given statistic is greaterthan the table value of that statistic, then thehypothesis is REJECTED.

Calculated value > Table value ( REJECT )

Calculated value < or = Table value ( RETAIN )


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Tails of a Test

For Null hypotheses two tailed test is applied.

For Non--directional hypotheses two tailed test is

applied.

For Directional hypotheses one tailed test isapplied.

Can you tell WHY ?????


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Statistical Significance

What is the significance of SIGNIFICANCE?

Levels of Significance---

1) 0.05 & 2) 0.01

Levels of Confidence---

1) 95 % & 2) 99 %

When to use the terms---

Significance & Confidence


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Types of Errors

Type I Error is committed when TRUE NULLhypothesis is REJECTED. ( alpha )

[Innocent is unjustly convicted or punished]

Type II Error is committed when NULLhypothesis is RETAINED, when it is notTRUE.

( Beta )

[Unjust acquittal of a guilty person]


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Steps of Testing Hypotheses

1) Frame the hypothesis.

2) Choose the appropriate statistical test.

3) Decide the level of significance.

4) Calculate value.

5) Refer to the appropriate table & get the critical value.

6) Compare both the values & decide about the

significance of your results.


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Some Major Statistical Tests

1) Chi square test

2) t test

3) Z test

4) F test


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Chi Square Test

Non-parametric test , used when the data is inthe nominal scale or grouped in the nominalcategories.

eg. YES NO

35 68

Do the people differ significantly in their opinion?


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Chi Square Test

Favourable Unfavourable

Men 53 37

Women 64 46

Do men & women differ significantly in theiropinions?


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Z Test & t - Test

Parametric tests are used when you want to

compare sample statistics of two groups.

Z test is used when the sample size is large (morethan 30 ) & t test is used when the sample size is

small (30 or less ).

Comparison of means, s.d., percentages of TWOgroups.


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F Test ( ANOVA)

Parametric test. When more than two groups

are to be compared F Test is applied.

ONE independent variable ONE WAY ANOVA

TWO independent variables TWO WAY ANOVA


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THANK YOU

data analysis 10

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