The nominal level is data that can be put in a category. The Ordinallevel is data that can be put in a category and put in order. The interval level is data that can be put in order and find differences between values. The ratio level is data that can be put in order, find differences between values, and find ratios of values.Answer: The nominal level is data that can be put in a category. The Ordinallevel is data that can be put in a category and put in order.
You are watching: Select all the levels of measurement for which data can be qualitative.
The statement is false. A true statement is “For data at the interval level, you can calculate meaningful differences between data entries.”
More types of calculations can be performed with data at the nominal level than with data at the interval level.
False. More types of calculations can be performed with data at the interval level than with data at the nominal level.
The level of measurement of data determines which statistical calculations are meaningful. The four levels of measurement, in order from lowest to highest, are nominal, ordinal, interval and ratio. The table below summarizes what calculations are meaningful for each level.Level of MeasurementPut data in categoriesArrange data in orderSubtract data valuesDetermine if one data value is a multiple of anotherNominalYesNoNoNoOrdinalYesYesNoNoIntervalYesYesYesNoRatioYesYesYesYesOK
The four levels of measurement, in order from lowest to highest, are nominal, ordinal, interval, and ratio.Data at the nominal level of measurement are qualitative only. Data at this level are categorized using names, labels, or qualities. No mathematical computations can be made at this level.Data at the ordinal level of measurement are qualitative or quantitative. Data at this level can be arranged in order, or ranked, but differences between data entries are not meaningful.Data at the interval level of measurement are quantitative only. Data at this level can be ordered and differences between data entries are meaningful, but a zero entry is not an inherent zero.Data at the ratio level of measurement are quantitative only. Data at this level are similar to data at the interval level, with the added property that a zero entry is an inherent zero.
Qualitative data consist of attributes, labels, or nonnumerical entries. Quantitative data consist of numerical measurements or counts.OK
What is an inherent zero? Describe three examples of data sets that have inherent zeros and three that do not.
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An inherent zero is a zero that implies none.Maximum wind speed during a hurricaneAverage monthly precipitation in inchesAverage age of college students in years
In an experiment, a treatment is applied to part of a population and responses are observed. The researcher in an experiment deliberately influences the responses.In an observational study, a researcher measures characteristics of interest of a part of a population but does not change existing conditions. The researcher in an observational study does not influence the responses.Next Question
With a random sample, each individual has the same chance of being selected.With a simple random sample, all samples of the same size have the same chance of being selected.Answer With a random sample, each individual has the same chance of being selected. With a simple random sample, all samples of the same size have the same chance of being selected.
Replication is repetition of an experiment under the same or similar conditions. Replication is important because it enhances the validity, or the accuracy and reliability, of the results.Next Question
A placebo is a fake treatment used in experiments. To minimize the possibility of the subjects reacting favorably to a placebo, the subjects will typically be blinded as to whether they are receiving a real treatment or the placebo.Next Question
Blinding is a technique in which the subjects of an experiment do not know whether they are receiving a treatment or the placebo. In a double-blind experiment, neither the experimenter nor the subjects know if the subjects are receiving a treatment or the placebo. The experimenter is informed after all the data have been collected.
A systematic sample selects members at regular intervals from a random starting point.OKFor stratified samples, members of the population are divided into two or more subsets, called strata. A sample is then randomly selected from each of the strata. This ensures that members of each group within the population will be sampled.Next Question
A systematic sample is a sample in which each member of the population is assigned a number. The members of the population are ordered in some way, a starting number is randomly selected, and then sample members are selected at regular intervals from the starting number.Next Question
What is an advantage of using a stem-and-leaf plot instead of a histogram? What is a disadvantage?
In a stem-and-leaf plot, each number is separated into a stem, such as the entry”s leftmost digits, and a leaf, such as the rightmost digit. There should be as many leaves as there are entries in the original data set and the leaves should be single digits. A stem-and-leaf plot is similar to a histogram but has the advantage that the graph still contains the original data. Another advantage of a stem-and-leaf plot is that it provides an easy way to sort data.OKAdvantage: Stem-and-leaf plots contain original data values where histograms do not. Disadvantage: Histograms easily organize data of all sizes where stem-and-leaf plots do not.
In a dot plot, each data entry is plotted, using a point, above a horizontal axis. A stem-and-leaf plot, each number is separated into a stem and a leaf.Both plots can be used to determine specific data entries.Your answer is correct.B.Both plots show how data are distributed.Your answer is correct.D.Both plots can be used to identify unusual data values.
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How is a Pareto chart different from a standard vertical bar graph?
The bars are positioned in order of decreasing height with the tallest bar on the left.
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