R Workflow Checklist

R Workflow Checklist

1. Planning

• Define research question
• Identify data sources
• Plan analysis steps

2. Setup

• Install required packages
• Load libraries
• Set working directory

3. Data

• Import data
• Clean data
• Check for errors

4. Analysis

• Run analysis
• Create visualizations
• Check results

5. Reporting

• Write findings
• Include code
• Add references

Checklist completed by: Fizza Zaheer

📋 R Workflow Checklist

Testing with sample data

✅ TEST 1: Create Sample Data

# Create simple data
test_data <- data.frame(
  ID = 1:5,
  Value = c(10, 20, 15, 25, 30)
)

# Show it
print("Test Data Created:")

## [1] "Test Data Created:"

print(test_data)

##   ID Value
## 1  1    10
## 2  2    20
## 3  3    15
## 4  4    25
## 5  5    30

✅ TEST 2: Basic Calculations

# Calculate mean
mean_value <- mean(test_data$Value)

# Calculate sum
total <- sum(test_data$Value)

cat("Mean:", mean_value, "\n")

## Mean: 20

cat("Total:", total, "\n")

## Total: 100

✅ TEST 3: Simple Visualization

# Create a bar plot
barplot(test_data$Value,
        names.arg = test_data$ID,
        main = "Sample Values by ID",
        xlab = "ID",
        ylab = "Value",
        col = "skyblue")

✅ Checklist Items Demonstrated:

• Created data frame ✓
• Performed calculations ✓
• Generated visualization ✓
• Displayed results ✓

—

Simple Regression Checklist

# Create data
set.seed(123)
study_data <- data.frame(
  Hours = sample(1:20, 30, replace = TRUE),
  Grade = sample(60:90, 30, replace = TRUE)
)
study_data$Score <- 50 + 2*study_data$Hours + 0.5*study_data$Grade + rnorm(30, 0, 5)

print("Data created successfully ✓")

## [1] "Data created successfully ✓"

# Fit model
model <- lm(Score ~ Hours + Grade, data = study_data)

print("Regression model:")

## [1] "Regression model:"

print(summary(model))

## 
## Call:
## lm(formula = Score ~ Hours + Grade, data = study_data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -7.5136 -3.6777  0.4743  2.8690  9.7157 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  45.4707     8.1510   5.579 6.47e-06 ***
## Hours         2.0517     0.1896  10.824 2.53e-11 ***
## Grade         0.5618     0.1030   5.454 9.02e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5.16 on 27 degrees of freedom
## Multiple R-squared:  0.8473, Adjusted R-squared:  0.836 
## F-statistic: 74.91 on 2 and 27 DF,  p-value: 9.585e-12

cat("All checks complete ✓\n")

## All checks complete ✓

• Data created
• Regression fitted
• Results displayed