Interpreting Statistical Data
Übersicht
Collecting data is only half the job. The real value comes from reading it well: spotting the message in a table, drawing fair conclusions from a chart, and knowing the difference between what the data shows and what it merely suggests. Good interpretation is a skill that protects you from being misled.
In this lesson you will read and draw inferences from tables and statistical diagrams, compare two data sets using both an average and a measure of spread, and learn the limits of what data can honestly tell you. These critical-thinking skills matter far beyond the exam, in any situation where numbers are used to make a case.
Ziele
- Read, interpret and draw inferences from tables and statistical diagrams.
- Compare sets of data using tables, graphs and statistical measures.
- Appreciate restrictions on drawing conclusions from given data.
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Herzlichen Glückwunsch zum Abschluss der Lektion über Interpreting Statistical Data. Jetzt, da Sie die wichtigsten Konzepte und Ideen erkundet haben,
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- A shop sells tea 24, coffee 36, juice 12 and water 8. How many drinks were sold in total? A. 68 B. 72 C. 80 D. 84 Answer: C
- Using those sales, what percentage of the drinks were coffee? A. 30% B. 36% C. 45% D. 50% Answer: C
- Class A has mean 60 and range 20; Class B has mean 60 and range 50. Which statement is correct? A. Class A performed much better on average B. The classes have the same average but A is more consistent C. Class B is more consistent D. The classes cannot be compared Answer: B
- Ice cream sales and drowning both rise in summer. What does this best illustrate? A. Ice cream causes drowning B. Drowning causes ice cream sales C. Correlation does not prove causation D. There is no link at all Answer: C
- Which is the most reliable basis for a conclusion about a whole country? A. A survey of 10 friends B. A survey of one town C. A large representative sample D. A single person's opinion Answer: C
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Lehrbuchabschnitt
Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs
One simple graph, the stem-and-leaf graph or stemplot , comes from the field of exploratory data analysis. It is a good choice when the data sets are small. To create the plot, divide each observation of data into a stem and a leaf. The stem consists of the leading digit(s), while the leaf consists
"Statistics: Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs" by OpenStax, OpenStax, Rice University, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Source: https://openstax.org/books/statistics/pages/2-1-stem-and-leaf-graphs-stemplots-line-graphs-and-bar-graphs. Access for free at https://openstax.org/books/statistics/pages/1-introduction
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Lehrbuchabschnitt
Measures of the Spread of the Data
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard devia
"Introductory Statistics: Measures of the Spread of the Data" by OpenStax, OpenStax, Rice University, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Source: https://openstax.org/books/introductory-statistics/pages/2-7-measures-of-the-spread-of-the-data. Access for free at https://openstax.org/books/introductory-statistics/pages/1-introduction
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