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Mind Map: Use of Statistical Tools | Economics Class 11 - Commerce PDF Download
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FAQs on Mind Map: Use of Statistical Tools - Economics Class 11 - Commerce
| 1. What are statistical tools and why are they important in research? |  |
Ans. Statistical tools are mathematical techniques used to analyze, interpret, and present data. They help researchers to summarize large amounts of data, identify patterns, test hypotheses, and make informed decisions. Their importance lies in providing a scientific basis for conclusions, ensuring that findings are valid and reliable.
| 2. What are some common statistical tools used in data analysis? | |
Ans. Some common statistical tools include descriptive statistics (like mean, median, mode), inferential statistics (such as t-tests, ANOVA), regression analysis, and statistical software (like SPSS, R, or Python libraries). Each tool serves different purposes, from summarizing data to testing relationships between variables.
| 3. How do you choose the right statistical tool for your data analysis? | |
Ans. Choosing the right statistical tool depends on the type of data you have (categorical vs. numerical), the research question, and the data distribution. For example, if you want to compare means, a t-test might be appropriate. It's also essential to consider the assumptions underlying each statistical method before making a selection.
| 4. What is the difference between descriptive and inferential statistics? | |
Ans. Descriptive statistics summarize and describe the main features of a dataset, such as calculating averages or percentages. In contrast, inferential statistics make predictions or inferences about a larger population based on a sample of data, often using techniques like hypothesis testing and confidence intervals.
| 5. Can statistical tools help in decision-making processes? | |
Ans. Yes, statistical tools are crucial in decision-making processes as they provide objective data analysis, allowing organizations to evaluate options, predict outcomes, and assess risks. By leveraging statistical insights, decision-makers can make more informed, evidence-based choices rather than relying on intuition alone.
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