Daily 1 - Jan 12

Class Performance

Students: 118 | Mean: 2.45 | Median: 2.5 | SD: 0.96

Scores ranged from 0.5 to 4.5 out of 5 points.

Score Distribution

Performance by Question

Questions

Q1: What does a histogram tell you?

A histogram shows the frequency distribution of continuous data — how many observations fall within each range/bin.

  • Confusing with time series (“data over time”)
  • Confusing with bar charts (“comparing categories”)
  • Confusing with box plots (mentioning quartiles)

Q2: What does standard deviation measure?

SD measures how spread out the data is from the mean — the average distance of data points from the center.

  • Confusing mean with median (“distance from the median”)
  • Confusing with residuals (“how far from predicted value”)
  • Confusing with IQR/range

Q3: What is a regression?

A regression is a statistical model that describes the relationship between variables — how independent variable(s) predict a dependent variable.

  • Using everyday meaning (“decline” or “going backwards”)
  • Confusing with hypothesis testing
  • Confusing with correlation

Q4: How do you estimate a regression?

Using Ordinary Least Squares (OLS) — finding coefficients that minimize the sum of squared residuals.

  • Naming tools instead of methods (“Excel,” “JMP”)
  • Circular answers (“regression analysis”)
  • High blank rate — most skipped question

Q5: How do you test significance of a coefficient?

Compare the p-value to alpha (typically 0.05). If p-value < alpha, the coefficient is statistically significant.

  • Comparing coefficient to a number (“if coefficient > 1”)
  • Using R² instead of p-value
  • Just naming the test without explanation

Key Takeaways

Strengths: SD measures spread from mean | p-value vs alpha | Regression models relationships

Review:

  • Histograms show frequency distribution — not time series or bar charts
  • OLS minimizes squared residuals — naming software doesn’t explain it
  • p < alpha → significant — compare p-value to 0.05