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Range Rule of Thumb Interpreting a Known Value of the Standard Deviation If the standard deviation of a collection of data is a known value, use it to find rough estimates of the minimum and maximum usual sample values as follows: minimum “usual” value = (mean) — 2 X (standard deviation) maximum “usual” value = (mean) + 2 X (standard deviation) Estimating a Value of the Standard Deviation s To roughly estimate the standard deviation from a collection of known sample data, use s === range/4 where range = (maximum data value) — (minimum data value). Empirical Rule A concept helpful in interpreting the value of a standard deviation is the empirical rule. This rule states that_/or data sets having a distribution that is approximately bellshaped, the following properties apply. (See Figure 3-3 on the next page.) About 68% of all values fall within 1 standard deviation of the mean. About 95% of all values fall within 2 standard deviations of the mean. About 99.7% of all va...

CVDOT many samples of data are large, so understanding them requires that we organize, summarize, and represent the data in a way that allows us to gain insight Characteristics of Data 1. Center: A representative value that indicates where the middle of the data set is located. 2. Variation: A measure of the amount that the data values vary. 3. Distribution: The nature or shape of the spread of the data over the range of values (such as bell-shaped). 4. Outliers: Sample values that lie very far away from the vast majority of the other sample values. 5. Time: Any change in the characteristics of the data over time. Frequency and Histogram Histogram is een grafische weergave van een frequency distirbiutie Assessing Normality: Normal Quantile Plot Some really important methods presented in later chapters have a requirement that sample data must be from a population having a normal distribution. We can see that a histogram is often helpful in determining whether the norm...

(uit elementary statistics) Parameter/Statistic A parameter ==> a numerical measurement describing some characteristic of a population. A statistic     ==> numerical measurement describing some characteristic of a sample. HINT The alliteration in “population parameter” and “sample statistic” helps us remember the meaning of these terms.   Quantitative/Categorical Quantitative (or numerical) data   ==> consist of numbers representing counts or measurements. Categorical (or qualitative or attribute) data  ==> consist of names or labels that are not numbers representing counts or measurements. Discrete/Continuous Quantitative data can be further described by distinguishing between discrete and continuous types. Discrete data ==>  result when the data values are quantitative and the number of values is finite or “countable.” (If there are infinitely many values, the collection of values is countable if it is possible to ...

(uit elementary statistics)   Prepare 1. Context What do the data mean? What is the goal of study? 2. Source of the Data Are the data from a source with a special interest so that there is pressure to obtain results that are favorable to the source? 3. Sampling Method Were the data collected in a way that is unbiased, or were the data collected in a way that is biased (such as a procedure in which respondents volunteerto participate)? I Analyze 1. Graph the Data 2. Explore the Data Are there any outliers (numbers very far away from almost all of the other data)? What important statistics summarize the data (such as the mean and standard deviation described in later)? How are the data distributed? Are there missing data? Did many selected subjects refuse to respond? 3. Apply Statistical Methods Use technology to obtain results. I Conclude 1. Statistical Significance Do the results have statistical significance? Do the results have practical significa...