Refer to the exercise identified and find the value of the test statistic. Exercise 6 "Cell Phon

step 1 The claim is made that fewer than 95 % of adults have a cell phone. In a merest poll of 1 ,128 a

Refer to the exercise identified and find the value of the...

Key Concepts

P-value

The p-value is the probability of obtaining an effect at least as extreme as the one observed from the sample data, assuming that the null hypothesis is true. It is a key measure in hypothesis testing and is compared with the significance level to decide whether the evidence is strong enough to reject the null hypothesis.

Significance Level

The significance level, often denoted by alpha, is the probability threshold used to determine whether to reject the null hypothesis. It represents the maximum allowable risk of making a Type I error, which is rejecting the null hypothesis when it is actually true, and is typically set at values like 0.05, 0.01, or 0.10.

Hypothesis Testing

Hypothesis testing is a statistical method used to make decisions or inferences about a population parameter based on sample data. It involves setting up a null hypothesis (typically a statement of no effect or difference) and an alternative hypothesis, then using the data to determine which hypothesis is more consistent with the observed evidence.

Test Statistic

A test statistic is a standardized quantity calculated from sample data, which is used in hypothesis testing to assess the compatibility of the observed data with the null hypothesis. Depending on the type of data and test being conducted, it could follow a known distribution such as the t-distribution or normal distribution, and it serves as the basis for determining the p-value or comparing against a critical value.

Standard Error

The standard error quantifies the variability or dispersion of a sample statistic, such as the mean, relative to the true population parameter. It is crucial in forming test statistics because it provides an estimate of the sampling distribution's spread, thereby reflecting the precision of the sample estimate in hypothesis testing.

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