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Analyzing Your Data

This analysis compares data from Alice and Bob to determine if their differences are due to random factors. It includes the evaluation of standard deviations, averages, and effect sizes, revealing crucial insights into the significance of the results. With Alice's data indicating a low probability (1%) of being influenced by chance, while Bob's data shows a 22% probability of random variance, this study highlights the importance of statistical testing in data interpretation. Use the provided links for detailed t-test exploration.

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Analyzing Your Data

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  1. Analyzing Your Data

  2. Was my difference caused by random factors?

  3. Bob’s Data

  4. Alice’s Data

  5. Alice’s Data Bob’s Data

  6. Alice’s Data Bob’s Data

  7. Alice’s Data C1 Standard Deviation: 2.05 C2 Standard Deviation: 0.82 Bob’s Data Average Standard Deviation: 1.73 Average Standard Deviation: 0.82 T1 Standard Deviation: 1.41 T2 Standard Deviation: 0.82

  8. Alice’s Data Effect Size > 1 = GOOD! Bob’s Data Average Standard Deviation: 1.73 Average Standard Deviation: 0.82 1 / 0.82 = 1.22 Effect Size = 1.22 1 / 1.73 = .58 Effect Size = .58

  9. t-Tests

  10. Alice’s Data http://vassarstats.net/tu.html Bob’s Data For Bob’s Data For Alice’s Data

  11. p =probability that your difference was due to random factors!

  12. Alice’s Data http://vassarstats.net/tu.html Bob’s Data p = .22 .22 > .05 (22% probability that Bob’s results are due to chance) p = .01 .01 < .05 (1% probability that Alice’s results are due to chance)

  13. Thank You&Happy Analyses!

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