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Hypothesis Testing

Procedures for 1-tail and 2-tail tests using Binomial Distributions

created October 12, 2025 updated June 1, 2026 2 min read

1-Tail Test Example

Null Hypothesis (H0H_0): The assumption that there is no effect or change.
Alternative Hypothesis (H1H_1): The claim we are testing for.

H0:p=12H1:p<12X∼B(10,12)where X represents the no. Heads thrown.\begin{aligned} H_0 &: p = \frac{1}{2} \\ H_1 &: p < \frac{1}{2} \end{aligned} \quad \quad X \sim B\left(10, \frac{1}{2}\right) \quad \text{where } X \text{ represents the no. Heads thrown.}

Result & Analysis

  • Result: x=2x = 2
  • Significance Level: 5%

Rule: We will reject H0H_0 if the probability of getting our result is less than our significance level.

P(x≤2)=0.0547(4 d.p)↑p-value\begin{array}{cl} P(x \leq 2) = 0.0547 & (4 \text{ d.p}) \\ \uparrow & \\ \text{p-value} & \end{array}

Definition: The p-value is the probability of obtaining a result as extreme as yours.

Conclusion:

  • 0.0547>5%0.0547 > 5\%, so we do not reject our model.
  • ∴\therefore NOT SIGNIFICANT and thus do not reject H0H_0.
  • At the 5% level, the evidence is not strong enough to suggest the coin is biased against heads.

2-Tail Test Example

H0:p=12H1:p≠12X∼B(10,12)where X represents the no. heads.\begin{aligned} H_0 &: p = \frac{1}{2} \\ H_1 &: p \neq \frac{1}{2} \end{aligned} \quad \quad X \sim B\left(10, \frac{1}{2}\right) \quad \text{where } X \text{ represents the no. heads.}

Result & Analysis

  • Significance Level: 5% (Note: In a 2-tail test, we compare the p-value to 2.5%2.5\% at each tail).
  • Result: 9 heads.
P(X≥9)=1−P(X≤8)=0.01070.0107<2.5%\begin{aligned} P(X \geq 9) &= 1 - P(X \leq 8) \\ &= 0.0107 \\ 0.0107 &< 2.5\% \end{aligned}

Conclusion:

  • ∴\therefore SIGNIFICANT and thus reject H0H_0.
  • At the 5% level, the evidence suggests the coin is biased. (It appears biased towards heads).