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Question 1:
You are given a dataset with information on the sales performance of a retail company across multiple regions. Using SAS, perform a descriptive statistical analysis to summarize the sales data. Include key measures such as mean, median, standard deviation, minimum, and maximum values. Provide insights into the sales distribution across different regions.
Answer 1:
To perform a descriptive statistical analysis using SAS, you can use the following code:
/* Import the dataset */
data sales_data;
/* Your dataset import code here */
run;
/* Descriptive statistics */
proc means data=sales_data;
var sales;
class region;
run;
This code imports your dataset into a SAS data set named ‘sales_data’ and then uses the ‘proc means’ procedure to calculate the mean, median, standard deviation, minimum, and maximum values of the variable "sales" for each region.
Question 2:
You have a dataset containing information about the performance of students in a graduate-level statistics course. Using SAS, perform a logistic regression analysis to predict the likelihood of a student passing the course based on variables such as study hours, prior experience in statistics, and attendance. Interpret the results and discuss the significance of each predictor.
Answer 2:
To perform a logistic regression analysis using SAS, you can use the following code:
/* Import the dataset */
data student_performance;
/* Your dataset import code here */
run;
/* Logistic regression analysis */
proc logistic data=student_performance;
model passed(event='1') = study_hours experience attendance;
/* Your other options and statements here */
run;
This code imports your dataset into a SAS data set named ‘student_performance’ and then uses the ‘proc logistic’ procedure to fit a logistic regression model. The dependent variable is "passed" (coded as 1 for passing and 0 for failing), and the independent variables are "study_hours," "experience," and "attendance." The ‘model’ statement specifies the logistic regression model.
Conclusion
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