Cell Phone Claim: Fewer than 95 % of adults have a cell phone. In a Marist poll of 1128 adults,

step 1 Cell phone claim. Fewer than 95 % of adults have a cell phone. In a merest poll of 1 ,128 adults

Cell Phone Claim: Fewer than 95 % of adults have a cell...

Key Concepts

One-Sided (One-Tailed) Test

A one-sided test is used when the research hypothesis predicts that the population parameter is either greater than or less than a certain value, but not both. It is relevant when the claim being tested is directional, as in the assertion that the proportion of the population with a certain attribute is less than a specified threshold.

p-Value

The p-value is a statistical metric that helps determine the strength of the evidence against the null hypothesis. It represents the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true. A smaller p-value indicates stronger evidence against the null hypothesis, which can lead to its rejection in favor of the alternative hypothesis.

Statistical Hypothesis Testing

This is a method used to decide whether there is enough evidence in a sample of data to infer that a certain condition is true for the entire population. It generally involves setting up a null hypothesis (which represents the status quo or a specific value for a parameter) and an alternative hypothesis (which represents a claim or an expected deviation from the null). The process then uses sample data to either reject or fail to reject the null hypothesis.

Sample Proportion

The sample proportion is the ratio of individuals in a sample that possess a specific characteristic, serving as an estimate of the corresponding proportion in the entire population. It is crucial in studies where the outcome is a binary variable, such as having or not having a cell phone, and it forms the foundation for inferential statistics in proportion-based hypothesis tests.

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