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Log-lin model
or growth model
Growth model:
• Growth indicates the magnitude of the rate of
change in the variable under consideration per unit
of time.
• Change in magnitude and also direction
• Note:
4
Growth rate:
Since the estimate of ‘b’ will be in log-linear function, the following
transformation will be used to convert it into the original form:
Precision of the estimates:
Significance of the growth rate will be tested by running Student’s t-test as given.
Where:
Precision of the estimates:
• Error Term: The variable in a simple or multiple regression
equation that contains unobserved factors that affect the
dependent variable. The error term may also include
measurement errors in the observed dependent or
independent variables.
• Standard error: It represents the average distance that the
observed values deviate from the regression line. In other
words, SE shows how wrong the regression model is on
using the units of the response variable.
• Standard deviation: It shows how much a given data is
spread out around the mean or average.

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Log lin or growth model

  • 2.
  • 3. Growth model: • Growth indicates the magnitude of the rate of change in the variable under consideration per unit of time. • Change in magnitude and also direction • Note:
  • 4. 4 Growth rate: Since the estimate of ‘b’ will be in log-linear function, the following transformation will be used to convert it into the original form:
  • 5. Precision of the estimates: Significance of the growth rate will be tested by running Student’s t-test as given. Where:
  • 6. Precision of the estimates: • Error Term: The variable in a simple or multiple regression equation that contains unobserved factors that affect the dependent variable. The error term may also include measurement errors in the observed dependent or independent variables. • Standard error: It represents the average distance that the observed values deviate from the regression line. In other words, SE shows how wrong the regression model is on using the units of the response variable. • Standard deviation: It shows how much a given data is spread out around the mean or average.