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Not really, the better expiriment would be if you used both sides of t he penny and compare all of your trials.
Draw a valid conclusion for that experiment.
Amy can assume that increasing the number of trusses increases the strength of the bridge.
repeated trials
When we say that the trials of an experiment are independent, it means that the outcome of one trial does not affect the outcome of any other trial. In other words, the results are not influenced by previous results, and each trial operates under the same conditions with the same probabilities. This independence is crucial for many statistical analyses, as it allows for valid conclusions to be drawn from the data collected.
A minimum of 6 sets of data are needed to make a valid conclusion.
To ensure an experiment's results are valid, you must conduct multiple trials to account for variability and increase reliability. This helps to minimize potential errors and ensure that the results are consistent and reproducible.
Not really, the better expiriment would be if you used both sides of t he penny and compare all of your trials.
Draw a valid conclusion for that experiment.
For the results of the experiment to be considered valid, a commonly accepted threshold is that they should be similar at least 70-80% of the time. This means that out of 17 trials, the results should align in at least 12 to 14 instances. Consistency in these results would bolster the reliability and validity of the experiment's findings.
Amy can assume that increasing the number of trusses increases the strength of the bridge.
cheese
repeated trials
When we say that the trials of an experiment are independent, it means that the outcome of one trial does not affect the outcome of any other trial. In other words, the results are not influenced by previous results, and each trial operates under the same conditions with the same probabilities. This independence is crucial for many statistical analyses, as it allows for valid conclusions to be drawn from the data collected.
The number of trials does not affect the result as each individual trial or experiment yields its own result caused by random small variations in the techniques used. What is affected is the conclusion derived from pooling all the individual results for the same type of trial and analysing the value obtained by statistical methods. It is generally reckoned that at least seven trials are required for the purpose of statistics and the analysis is commonly expressed as the Mean (average value) and Standard Deviation, (a number that reflects the extent of the variation between the individual trials). However, different statistical methods are used for analysing different types of data, the commonest reflecting the difference between parametric (the variation is the same on both sides of the mean) and non-parametric (The spread of variation is greater on one side of the mean than the other). Obviously a considerable number of individual trials is required to be able to make a valid distinction between the two.
A control is needed in a valid experiment because without controls then more then one variable is being tested. This can mess up the results.
when he or she's conclusion is right