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T - Test
Business Analytics
Types of T-Test
• One Sample T-Test (Only one Metric Data)
• Independent Sample T-Test (One Categorical data with two groups
and one metric data)
• Paired T-Test (Both the data are Metric and are from same sample units)
Assumptions for T-Test
•Data is normally Distributed
•The sampling Technique used is random sampling technique
Type of Tests
Dependent
Variable
Dependent Variable
Categorical Metric
Independent
Variable
Categorical Chi Square
2) Independent Sample T-test (2
Groups) Example: (High/Low),
(Girl/Boy)
2) ANOVA (More than two
groups)
Independent
Variable
Metric
Logistic
Regression
3) Paired T-Test (Pre and
PostTest)
2) Correlation
or
Regression
One Sample T-Test
(Only one Metric Data)
Univariate Analysis
Case 1
• A lathe machine underwent repair and the production
manager needs clarity on the functioning of the machine
that makes, stainless steel rings.
• Data Available
– We have sample readings of a lathe machine in microns for 452
units.
– Historic data, we have average (Mean) reading for a month, of
units been produced. ie, 3010 microns
• To examine if there is any variation in the Lathe Machine,
after making a repair
⁃ H0: There is no difference in mean scores of the
population mean and sample mean
⁃ H1: There is difference in mean scores of the
population mean and sample mean
Objective for the Study
Hypothesis for the test
H0:  Sample   Population
H1:  Sample   Population
Independent Sample T-
Test
(One Categorical data with two groups, and one metric data)
Case 2
• 450 respondents are asked to give their opinion towards the aspect
of waste management. The aspect of waste management confines 10
statements and the data is collated on 7 point scale.
• The researcher needs understanding, whether the respondents
opinion are uniform, considering gender as independent variable
• Data Available
– Gender of students (Boys and Girls)
– The added value of 10 elements that has framed a construct
• To assess the uniformity in the responses towards the aspect
of waste management
⁃ H0: There is no difference in mean scores of the
respondents towards the aspect of waste management
⁃ H1: There is difference in mean scores of the
respondents towards the aspect of waste management
Objective for the Study
Hypothesis for the test
H0:  Boys   Girls
H1:  Boys   Girls
Paired T-Test
(Both the data are Metric and are from same sample units)
Case 3
• Students underwent classes on “Business Analytics”.
However the lecturer needs to know whether or not the
classes have influenced their understanding on the
concepts. Assessment tests was carried out before the
course and after the course.
• Data Available
– Pre and Post Test Marks of 754 students
• To assess the influence of Business Analytics classes amidst
students
⁃ H0: There is no difference in mean scores of pre
and post test assessment
⁃ H1: There is difference in mean scores pre and post
test assessment
Objective for the Study
Hypothesis for the test
H0:  Pre Test   Post Test
H1:  Pre Test   Post Test

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T Test.pptx

  • 1. T - Test Business Analytics
  • 2. Types of T-Test • One Sample T-Test (Only one Metric Data) • Independent Sample T-Test (One Categorical data with two groups and one metric data) • Paired T-Test (Both the data are Metric and are from same sample units) Assumptions for T-Test •Data is normally Distributed •The sampling Technique used is random sampling technique
  • 3. Type of Tests Dependent Variable Dependent Variable Categorical Metric Independent Variable Categorical Chi Square 2) Independent Sample T-test (2 Groups) Example: (High/Low), (Girl/Boy) 2) ANOVA (More than two groups) Independent Variable Metric Logistic Regression 3) Paired T-Test (Pre and PostTest) 2) Correlation or Regression
  • 4. One Sample T-Test (Only one Metric Data) Univariate Analysis
  • 5. Case 1 • A lathe machine underwent repair and the production manager needs clarity on the functioning of the machine that makes, stainless steel rings. • Data Available – We have sample readings of a lathe machine in microns for 452 units. – Historic data, we have average (Mean) reading for a month, of units been produced. ie, 3010 microns
  • 6. • To examine if there is any variation in the Lathe Machine, after making a repair ⁃ H0: There is no difference in mean scores of the population mean and sample mean ⁃ H1: There is difference in mean scores of the population mean and sample mean Objective for the Study Hypothesis for the test H0:  Sample   Population H1:  Sample   Population
  • 7. Independent Sample T- Test (One Categorical data with two groups, and one metric data)
  • 8. Case 2 • 450 respondents are asked to give their opinion towards the aspect of waste management. The aspect of waste management confines 10 statements and the data is collated on 7 point scale. • The researcher needs understanding, whether the respondents opinion are uniform, considering gender as independent variable • Data Available – Gender of students (Boys and Girls) – The added value of 10 elements that has framed a construct
  • 9. • To assess the uniformity in the responses towards the aspect of waste management ⁃ H0: There is no difference in mean scores of the respondents towards the aspect of waste management ⁃ H1: There is difference in mean scores of the respondents towards the aspect of waste management Objective for the Study Hypothesis for the test H0:  Boys   Girls H1:  Boys   Girls
  • 10. Paired T-Test (Both the data are Metric and are from same sample units)
  • 11. Case 3 • Students underwent classes on “Business Analytics”. However the lecturer needs to know whether or not the classes have influenced their understanding on the concepts. Assessment tests was carried out before the course and after the course. • Data Available – Pre and Post Test Marks of 754 students
  • 12. • To assess the influence of Business Analytics classes amidst students ⁃ H0: There is no difference in mean scores of pre and post test assessment ⁃ H1: There is difference in mean scores pre and post test assessment Objective for the Study Hypothesis for the test H0:  Pre Test   Post Test H1:  Pre Test   Post Test