Table of contents

1. Introduction to Accounting1h 21m
2. Transaction Analysis1h 13m
3. Accrual Accounting Concepts2h 38m
4. Merchandising Operations2h 30m
5. Inventory1h 55m
6. Internal Controls and Reporting Cash1h 16m
7. Receivables and Investments3h 8m
8. Long Lived Assets5h 1m
9. Current Liabilities2h 19m
10. Time Value of Money1h 23m
- Time Value of Money Equations
  35m
- Using Time Value of Money Tables
  47m
11. Long Term Liabilities2h 45m
12. Stockholders' Equity2h 15m
13. Statement of Cash Flows2h 24m
14. Financial Statement Analysis5h 25m
15. GAAP vs IFRS56m

14. Financial Statement Analysis

Introduction to Ratios

Financial Accounting

14. Financial Statement Analysis

Introduction to Ratios

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Multiple Choice

1. Why do financial analysts use hypothesis testing when analyzing financial ratios?

To eliminate the need for any further financial analysis.

To ensure that all ratios are always equal across different companies.

To automatically increase the profitability of a company.

To determine if observed differences in ratios are statistically significant and not due to random chance.

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Verified step by step guidance

Understand the concept of hypothesis testing: Hypothesis testing is a statistical method used to determine whether there is enough evidence to support a specific claim or assumption about a population parameter, such as financial ratios.

Recognize the purpose in financial analysis: Financial analysts use hypothesis testing to assess whether observed differences in financial ratios between companies or over time are statistically significant, meaning they are unlikely to have occurred due to random chance.

Formulate hypotheses: Analysts typically set up a null hypothesis (H₀), which assumes no significant difference in the financial ratios, and an alternative hypothesis (H₁), which suggests there is a significant difference.

Perform statistical tests: Analysts collect data on financial ratios and apply appropriate statistical tests, such as t-tests or ANOVA, to evaluate the hypotheses. These tests help determine whether the null hypothesis can be rejected based on the data.

Interpret results: Based on the p-value or test statistic obtained, analysts decide whether the observed differences in financial ratios are statistically significant. This helps them make informed decisions about the financial health or performance of companies.