**Table Explanation: Decision Making with α and P Values**The table below shows different α (alpha) values and hypothetical P values to help determine whether to accept or reject a null hypothesis in statistical testing.| α | P | Decision ||------|---------|-------------------------------------------------|| 0.05 | 0.06 | 0.06 > 0.05 accept the null hypothesis || 0.01 | 0.012 | || 0.001| 0.0001 | || 0.05 | 0.045 | || 0.01 | 0.1 | || 0.05 | 0.051 | || 0.10 | 0.09 | 0.09 < / = 0.10 fail to accept the null hypothesis|**Explanation:**- **α (Alpha) Value**: The significance level, usually set at 0.05, 0.01, or 0.001, denotes the threshold for rejecting the null hypothesis.- **P Value**: The probability of observing the data given that the null hypothesis is true. It helps determine whether the data provides enough evidence to reject the null hypothesis.- **Decision**: Based on the comparison between the P value and the α value: - If P > α, accept the null hypothesis. - If P ≤ α, fail to accept the null hypothesis (often implying the data is significant).In the table, specific examples illustrate these decision-making rules, emphasizing how different combinations of α and P values influence hypothesis testing decisions.

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MATLAB: An Introduction with Applications

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Below are some a values, and hypothetical P values. Should you accept or reject the null hypothesis? P .05 .06 .06>.05 accept the null hypothesis .01 .012 .001 .0001 .05 .045 .01 .1 .05 .051 .10 .09 .09=.10 fail to accept the null hypothesis