Question

question 12 (1 point) what statement is not true about the levels of measurements in statistics: they tell us how data can be collected, analyzed and interpreted they support different statistical analyses they tell us which hypothesis tests are possible they can determine the most effective type of data visualization they require that all data be measured in whole numbers only

Explanation:

Step1: Analyze each option

• Option 1: Metrics do not require all data to be measured in whole numbers. For example, in calculating the average of a set of data, the values can be fractions or decimals.
• Option 2: Metrics help in determining the most effective type of data visualization. Different metrics (e.g., mean, median, mode for numerical data; frequency counts for categorical data) guide the choice of visualizations like histograms, bar charts etc.
• Option 3: Metrics (e.g., test - statistics in hypothesis testing) tell us which hypothesis tests are possible. For example, if we have a metric like the standard deviation of a sample, it helps in choosing between a z - test and a t - test.
• Option 4: Metrics support different statistical analyses. For example, the correlation coefficient (a metric) is used in regression analysis.
• Option 5: Metrics (e.g., sample size, variance) tell us how data can be collected, analyzed and interpreted. For example, a large variance might suggest the need for a larger sample size.

Answer:

They require that all data be measured in whole numbers only.