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Observed results can arise from both chance and mathematical processes. Statistical methods help determine whether results are significant or likely due to random variation. By using probability and hypothesis testing, researchers can assess the likelihood that observed outcomes are genuine effects rather than random occurrences. Ultimately, the interpretation often depends on the context and the rigor of the analytical methods employed.
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Are expected results due to chance or are they arrived at mathematically?
Expected results can arise from both chance and mathematical calculations. In probabilistic contexts, expected values are calculated using mathematical formulas based on probabilities and outcomes. However, in experimental settings, observed results may also reflect random variations or chance. Therefore, while mathematical methods provide a framework for predicting expected results, actual outcomes can be influenced by stochastic factors.
At a significance level of 0.01 which conclusion can the brewer draw?
That there is a 99% chance that the results of the brewer's study happened because of his manipulation of the IV and not by chance
Why are researchers so careful about drawing conclusions regarding statistical significance?
They want to make sure an observed difference isn't due to chance
Is alpha the probability that the test statistic would assume a value as or more extreme than the observed value of the test?
Alpha is the probability that the test statistics would assume a value as or more extreme than the observed value of the test, BY PURE CHANCE, WHEN THE NULL HYPOTHESIS IS TRUE.
What does it mean to find the expected value of a chance activity with numerical outcomes?
I think it means to find the theoretical probability of something random that has results that are numbers. For instance, rolling a die and trying to get a 6 is a "chance activity with numerical outcomes".
Are expected results due to chance or are they arrived at mathematically?
Expected results can arise from both chance and mathematical calculations. In probabilistic contexts, expected values are calculated using mathematical formulas based on probabilities and outcomes. However, in experimental settings, observed results may also reflect random variations or chance. Therefore, while mathematical methods provide a framework for predicting expected results, actual outcomes can be influenced by stochastic factors.
Why is replication important in experimental?
Observed results are less likely to be affected by random chance.
Why is replication in experimental design?
Observed results are less likely to be affected by random chance.
Why is replication important and experimental design?
Observed results are less likely to be affected by random chance.
The term statistical significance implies that the results are?
The observed value is unlikely to have occured purely bt chance under the null hypothesis and, as a consequence, you ought to reject the null in favour of the alternative hypothesis.
What is random variation?
Random variation refers to the natural variability observed in data that arises due to chance or random factors. It can impact the results of experiments, making it important to account for this variability when drawing conclusions from data. Random variation is often controlled for using statistical methods to ensure that patterns or effects observed are not simply due to chance.
What type of tests are used to compare date from an experiment to determine if results are due to chance?
To determine if experimental results are due to chance, researchers commonly use statistical tests such as t-tests, ANOVA (Analysis of Variance), and chi-square tests. These tests evaluate the differences between groups or variables and assess the likelihood that observed differences occurred by random variation. The results are typically interpreted using p-values, where a p-value below a predetermined threshold (commonly 0.05) indicates that the results are statistically significant and unlikely to be due to chance.
What does The first law of probability state?
States that the results of one chance event have no effect on the results of subsequent chance events.
What is meant by observed genotypes?
A phenotype is a physical characteristic. For a human an observed phenotype example would be hair colour (e.g brown) or eye colour (green). An observed phenotype is a physical characteristic that can be seen directly or indirectly (internal organs) caused by an individual's genotype.
What is this called when you experiment more than once to reduce chance of errors this is called?
When you experiment more than once to reduce the chance of errors, this is called "replication." Replication helps ensure that results are reliable and not due to random chance or experimental error. It enhances the validity of the findings by confirming that similar outcomes are consistently observed under the same conditions.
Why have a null hypothesis?
Statistical tests are designed to test one hypothesis against another. Conventionally, the default hypothesis is that the results were obtained purely by chance and that there is no observed effect acting on the observations - ie the effect is null. The alternative is that there IS an effect.
What is experimental variation?
Experimental variation refers to the differences in outcomes or results that are observed between different trials or groups within an experiment. These variations can arise due to factors such as measurement errors, environmental conditions, or random chance. Minimizing experimental variation is important to ensure the reliability and validity of the experimental results.
