MY

1.3 basic stats pt2

types of data

continuous data

  • no discrete measurement

    • eg height, time, weight

  • use line graph

discrete data

  • categorical

    • eg type of fruit or number of students

  • use bar graph

types of hypotheses

hypothesis

  • educated guess or prediction to explain an observation

  • what you think will happen

  • sometimes as if/then/because statements

null hypothesis

  • counter to a hypothesis

  • statement of “no effect”

  • can be tested w stats

chi square analysis

\char"03A7 ^2=\Sigma\frac{\left(o-e\right)^2}{e}

“goodness of fit”

  • how well does data fit experimental expectations?

  • is null hypothesis supported?

only used w/ discrete data

chi² = summation of (observed - expected)²/expected

more stats

degrees of freedom

  • n-1

p-values

  • 0.05 or 0.01

  • probability of statistical significance

critical value

  • comparison point for X²

Interpreting results

  • If X² < CV

    • observed vs expected values are NOT statistically significantly different

    • accept the null hypothesis

  • If X² < CV

    • observed vs expected values ARE statistically significantly different

    • reject the null hypothesis