- Write a short research scenario that appropriate for using the statistical procedures and address the followings: (ANCOVA and Logistic regression)
Please use each method to write short scenario:
ANCOVA:
Doesn’t need DATA… it is just a ‘scenario’ from imagination for example if we use to choose (ANCOVA) then all questions we answer them depends on ANCOVA assumption or role of ANCOVA.
First describe scenario in here
a. Type of research design and justification of the choice (what type of experiment For example, is it quasi experiment or true experiment longitudinal design .etc.).
b. Population Description of population.
c. Target population: For example ( all high school students in USA)
d. Accessible population: For example ( all Dr.phillips high school students in Orlando)
e. Type of Sample: (which sampling is an appropriate for this scenario is it random sampling, snowball sampling, cluster sampling .etc.)
f. justifying sampling technique, and limitations of sample (if any), etc.
g. Research Question: For example ( Are there temperature effect on the size of plant after controlling for age differences?)
H0: for example ( there differences in the means of the groups after controlling for 1 or more continuous variables)
H1: (there is no differences in the means of the groups after controlling for 1 or more continuous variables)
h. Variables: Define major variables: independent and dependent variables and their relationship to instrument. Explain how they will be coded.
For example (ANCOVA),
IV (should be categorical) = teaching method ( you should use optimization definition be specific)
DV (continuous) = academic achievement ( you should use optimization definition be specific)
CV (continuous) = motivation ( you should use optimization definition be specific)
Experimental design – assume students randomly allocated to different teaching methods.
i. Data Analysis For each research question and hypothesis, how you will analyze the data,
j. which statistic you will use (and justify this choice),
( I will use ANCOVA because …. )
k. what p value you intend to use and why,
l. and what assumptions do you need to check and how to know if met or not ?
For example ( 1- Normality assumption: I will use histogram or Shapiro wilks if p-value is greater than .05 that mean met. . 2- homogeneity of variance: I will use Leven’s test table 3- Homo of regression I will use scatterplot 4- linearity: I will use p-plot if we have street line that mean is met ..etc.)
m. Reliability & Validity: Address how you will assure these aspects of research.
n. What tests for collinearity, homogeneity, normal distribution, etc. will you use?
This is example of ANCOVA:
Again :
IV (should be categorical) = teaching method ( you should use optimization definition be specific)
DV (continuous) = academic achievement ( you should use optimization definition be specific)
CV (continuous) = motivation ( you should use optimization definition be specific)
- Write a short research scenario that appropriate for using the statistical procedures and address the followings: (ANCOVA, Logistic regression,)
Please use each method to write short scenario:
Logistic Regression:
Doesn’t need DATA… it is just a ‘scenario’ from imagination for example if we use to choose Logistic Regression then all questions we answer them depends on Logistic Regression assumption or role of Linear Regression.
First describe scenario in here
a. Type of research design and justification of the choice
b. Population Description of population.
c. Target population: For example
d. Accessible population: For example
e. Type of Sample:
f. justifying sampling technique, and limitations of sample (if any), etc.
g. Research Question:
H0:
H1:
h. Variables: Define major variables: independent and dependent variables and their relationship to instrument. Explain how they will be coded.
i. For example Linear Regression
j. Data Analysis For each research question and hypothesis, how you will analyze the data,
k. which statistic you will use (and justify this choice),
l.
m. what p value you intend to use and why,
n. and what assumptions do you need to check and how to know if met or not ?
o. Reliability & Validity: Address how you will assure these aspects of research.
p. What tests for collinearity, homogeneity, normal distribution, etc. will you use?
This is example of Linear Regression: