Day 10: CFA Level I Hypothesis Testing Foundations Study Plan

Today’s CFA Level I study focuses on hypothesis testing.  Today’s goal is to understand how analysts use sample evidence to make careful decisions without overstating certainty. Understand the basic structure of a hypothesis test: null hypothesis, alternative hypothesis, test statistic, significance level, p-value, and decision rule. The focus should be on interpretation first, then calculation.

This is a study plan and blog draft, not official CFA Institute curriculum material. Use it to guide your preparation, then rely on your CFA notes, curriculum, or question bank for the actual readings and practice questions.

Checklist pre - study

Spend 10-15 minutes setting up before you begin.

• Workspace: Prep a clean workspace with notebook ready
• Formula sheet: Mark formulas for test statistic, standard error, confidence interval, and p-value interpretation.
• Flash cards: Keep flash cards ready to fill or filled
• Calculator: Clear previous statistics entries and keep your normal distribution or z-table reference ready if you use one.
• Question bank setup: Create or filter a set called “Day 10 Hypothesis Testing.”
• Time block: Plan 90 minutes total: 15 minutes prep, 60 minutes study and practice, 15 minutes review.

Today’s goal is not to memorize every test immediately. The first goal is to understand the logic: claim, evidence, decision, and interpretation.

Daily Ethics reading and prep

Spend 10-15 minutes on Ethics before the Quant block.

Today’s Ethics focus: misleading conclusions from weak evidence.

Read or create one short scenario where an analyst makes a strong recommendation based on limited data. Then ask:

• Is the sample large enough to support the conclusion?
• Has the analyst explained uncertainty?
• Are assumptions disclosed?
• Is the language too certain?
• Could a client be misled by the conclusion?

Then complete 5 Ethics warm-up questions or scenario checks. For any missed Ethics question, classify it mainly as Concept gap or Reading error.

Main study block

Today’s Quantitative Methods focus is hypothesis testing foundations.

Study these subtopics:

• Null hypothesis: The default claim or status quo being tested.
• Alternative hypothesis: The claim you are looking for evidence to support.
• One-tailed test: Used when the alternative points in one direction.
• Two-tailed test: Used when the alternative allows movement in either direction.
• Test statistic: A standardized measure of how far the sample result is from the hypothesized value.
• Significance level: The threshold for rejecting the null hypothesis.
• p-value: The probability of observing evidence as extreme as the sample result, assuming the null is true.
• Type I error: Rejecting a true null hypothesis.
• Type II error: Failing to reject a false null hypothesis.
• Decision rule: The process for deciding whether to reject or fail to reject the null.

A useful rule for today: do not say “accept the null.” Say fail to reject the null. This wording matters because a test may not prove the null is true; it may only show that the evidence is not strong enough to reject it.

25-question practice target

Complete 25 questions today.

Use this breakdown:

• 4 questions: Identify null and alternative hypotheses
• 4 questions: One-tailed versus two-tailed tests
• 4 questions: Test statistic interpretation
• 3 questions: Significance level and rejection rules
• 3 questions: p-value interpretation
• 2 questions: Type I and Type II errors
• 5 questions: Ethics warm-up on evidence, disclosure, and misleading conclusions

For every Quant question, write the decision in plain English after solving. For example: “There is enough evidence to reject the null,” or “There is not enough evidence to reject the null.”

Mistake-log prompt

Log every missed or guessed question using exactly one of these labels:

• Concept gap: I did not understand the testing idea or decision logic.
• Formula gap: I understood the logic but forgot the formula or used the wrong setup.
• Calculator error: I made an arithmetic, table, or input error.
• Reading error: I misunderstood the wording, tail direction, significance level, or conclusion.

For Ethics mistakes, use mainly Concept gap or Reading error.

Five-question review checkpoint

Answer these without notes at the end of the session:

1. What is the difference between the null hypothesis and the alternative hypothesis?
2. When should a test be one-tailed instead of two-tailed?
3. What does a p-value tell you in plain language?
4. What is the difference between Type I and Type II error?
5. Why should you say “fail to reject the null” instead of “accept the null”?

The main lesson from Day 10 is that hypothesis testing is not just math. It is a discipline for making claims carefully. A good analyst does not just calculate a result; they explain what the evidence does and does not support.

Tomorrow preview

Day 11 will continue hypothesis testing with confidence intervals, test statistics, rejection regions, and more practice in translating numerical results into clear conclusions.