Learn how to import data from text and Excel files into SAS, name and locate your data, specify year and rent price columns, and run the import process.

Learn to import a csv into sas by specifying the dataset name and file path, setting variable formats, and converting Excel to csv for clean data.

Learn to hard-code a simple SAS dataset by using input to create numeric variables height and weight, add a character name variable, and display results with proc print.

Export data in SAS OnDemand by importing a spreadsheet, creating a data set, and using proc export to produce a CSV file, then download it to your local computer.

learn to export SAS data to two formats using proc export: csb (excel) and a text file, ensuring the data persists after exiting SAS.

Learn how to print data in SAS by printing a specified table or the last modified data table, including creating a new dataset and modifying it for output.

Create a new dataset and a variable to store the calculation results, compute the average rent as the criterion, and append a performance column to compare yearly values.

Learn how to sort SAS data using proc sort in ascending and descending order, output to a new table, and print results with proc print.

Learn how to use the SAS library with libname to manage data efficiently, turning folders into accessible SAS data sets and excluding Excel files that aren’t recognized.

Learn how SAS comments work, including block comments marked by slash-star at the start and end, and star comments that begin with a star and end with a command.

Learn how to report data contents with SAS PROC CONTENTS to obtain dataset metadata. Identify variable types and structure, especially for large Excel datasets.

Describe dataset statistics with the SAS means procedure to obtain mean, standard deviation, minimum, maximum, and 5 percent to 95 percentiles for the rent variable.

Apply proc corr in SAS to compute Pearson correlation coefficients between variables in rent data. Note the diagonal ones and symmetry, and select pairs with the ras command.

Explore the basics of linear regression, including simple and multiple regression, with the dependent variable y and explanatory variables x, and the meaning of regression coefficients.

Explore how to interpret SAS results by examining the parameter estimates table for regression coefficients, including the intercept and the X coefficient, and assess model fit with p-values and R-squared.

Learn how to extend regression analysis in SAS by requesting residuals and predicted values, storing them in new variables, and printing to evaluate model fitness.

Learn how to transition from simple to multiple regression by including multiple explanatory variables, examine results, and interpret the square and adjusted square for model validity.

Interpret multiple regression results by using adjusted r square to penalize irrelevant variables and examining the p values in the parameter estimates table to assess significance.

Learn to use SAS regression on a data table to make predictions from existing observations, including manually adding data with the input command and reading the predicted value.

Explore how scatter plots reveal the relationship between temperature and beach visitors, showing an upward trend, and how bar plots and pie plots express values and composition.

Import data, set up proc gplot, define a dot symbol, no line between points, and plot vacancy rate (y) versus square footage (x) to create a scatter plot.

Learn to create a series plot in SAS by turning a scatter plot into a line-connecting chart, emphasizing sorting data with Proc Sort by square footage to improve the visualization.

Learn to create bar plots and pie plots in SAS using g chart with vbar and hbar options, plot age data, and display frequency, cumulative frequency, and percentages.

Learn to overlay plots in SAS gplot by plotting vacancy rate versus age and operating expenses versus age on a single graph, then add a top-center legend.

Explore SAS SQL to manipulate databases with a flexible structured query language, work with data sets, and practice creating and executing commands toward merging operations.

Learn how to select columns in SAS, from a single variable to multiple variables, or all variables with a star, using the purchase dataset as examples.

Count observations in a dataset using count, and rename the result column. Practice simple from and select examples, then see how count integrates with other functions for power.

Learn how to select distinct values in SQL using the distinct function to remove duplicates, count distinct areas and customers, and combine distinct with other functions.

Learn how the group by command classifies observations into subgroups by a key variable such as area and applies the count function to each subgroup.

Learn to store SAS procedure results by creating a new table with create table, selecting desired columns, and using distinct to capture unique customer names.

Master the SAS print procedure to format columns with SAS formats, group observations by provinces, and generate subtotals for each province in a detailed report.

Learn to produce detailed SAS reports with the print procedure. Import data, limit observations with obs=, and remove the extra column using notes.

Explore enhanced detailed report (part 1) techniques in SAS: use the print procedure to select columns, apply where filters, format profit as dollars, and add a report title.

Learn to create a province-level SAS report showing profits by sorting data, using a by-province print, and the d command to combine provinces into one table.

Learn sas macro basics, where macros are programs with a percent sign that automate tasks, mimic print and summary procedures, generate descriptive statistics, and trim outliers to save time.

Learn how to create and use SAS macro variables to store values, print and reference them in procedures, and easily switch dataset and variable lists by redefining a single macro.

Define a SAS macro function using the percent sign and rename foobar to my_func. Name and call the parameters with equal signs and apply default values when not specified.