Studio R Project
Budget: €8 – €30 EUR
Hello, i would need this project done in the next 1-2 days. It should not be complicated. Let me know if you are up to it. .sav document Is attached.
Here is what needs to be done:
Dataset: ISSP_Env_2020_reduced_FINAL
Variables: v20, v50
v20: Modern science will solve our environmental problems with little change to our way of life [1 = agree
strongly/strongly agree; 5 – strongly disagree; 6 = no answer]
v50: In a typical week, on how many days do you eat beef, lamb, or products that contain them?
[0 – 7 = number of days, 8 = no answer]
Preparation:
• Set a working directory
• Load all relevant packages
• Read the ISSP data set ISSP_Env_2020_reduced_FINAL
• Check the two variables for missing data (NAs). Just take into account
complete cases and close incomplete cases within the two
Variables with the drop_na() command at the beginning before starting the analysis.
• Based on the scale level, explain the requirements for chosen
Position and dispersion measures as well as statistical tests.
• Formulate the hypotheses for the chosen statistical test.
• If there is no normal distribution, there is no homogeneity of variance
check.
• Work with a significance level of α = 0.05 and use
two-tailed tests.
Tasks:
a) Determine the data type of both variables and look at the variables
initially descriptive (location and dispersion measures, frequency analysis). Determine
the scale level of both variables.
b) Recode the variable v50. Create a new variable “meatcon” that
contains the following information: 0 = up to once per week, 1 = more than once per week
Week. Remember to do a frequency analysis after recoding
to check whether the recoding is correct. (Note: concerns
In the process, select the data type of the variable!)
c) Use an appropriate parametric or non-parametric test to check
whether there is a difference between the two groups regarding the central
Tendency (statement on lifestyle change; v20).
Here is what needs to be done:
Dataset: ISSP_Env_2020_reduced_FINAL
Variables: v20, v50
v20: Modern science will solve our environmental problems with little change to our way of life [1 = agree
strongly/strongly agree; 5 – strongly disagree; 6 = no answer]
v50: In a typical week, on how many days do you eat beef, lamb, or products that contain them?
[0 – 7 = number of days, 8 = no answer]
Preparation:
• Set a working directory
• Load all relevant packages
• Read the ISSP data set ISSP_Env_2020_reduced_FINAL
• Check the two variables for missing data (NAs). Just take into account
complete cases and close incomplete cases within the two
Variables with the drop_na() command at the beginning before starting the analysis.
• Based on the scale level, explain the requirements for chosen
Position and dispersion measures as well as statistical tests.
• Formulate the hypotheses for the chosen statistical test.
• If there is no normal distribution, there is no homogeneity of variance
check.
• Work with a significance level of α = 0.05 and use
two-tailed tests.
Tasks:
a) Determine the data type of both variables and look at the variables
initially descriptive (location and dispersion measures, frequency analysis). Determine
the scale level of both variables.
b) Recode the variable v50. Create a new variable “meatcon” that
contains the following information: 0 = up to once per week, 1 = more than once per week
Week. Remember to do a frequency analysis after recoding
to check whether the recoding is correct. (Note: concerns
In the process, select the data type of the variable!)
c) Use an appropriate parametric or non-parametric test to check
whether there is a difference between the two groups regarding the central
Tendency (statement on lifestyle change; v20).