What Is An Observational Unit – 2 Statistics is the study of data, the science of reasoning from data. What does the word data mean? You will find that information varies and the variation increases in everyday life. Observational Unit – is the object described in the data collection. Variation – a variable phenomenon that takes different values or parts of one parameter compared to another. Numeric variables – take numeric values whose numeric operations make sense. Such as height, weight, time, … Different variables – put an individual into one of several categories or several categories. Such as gender, Oklahoma cities, US states, … Binary variables – different variables that can only take two possible outcomes. Male/female, Yes/No, … Research question – usually looks for patterns in a variable or compares a variable between different groups or looks for a relationship between variables.
The distinction between categorical and quantitative variables is very important in determining which statistical tools to use in analyzing a given data set. Decide if the data is measured quantitatively or specifically How many hours you slept in the last 24 hours If you slept at least 7 hours in the last 24 hours according to your postal code, … Warning: to determine whether something is truly variable, ask yourself whether it represents a question that can be asked for each unit of observation and whether values can vary from one unit of observation to another.
What Is An Observational Unit
Data are not just numbers Data are collected with purpose and meaning in a particular situation The core concept of statistics is variability As we progress through the course, you will understand how to classify variables and determine the tools Statistically applicable data Always consider. contextual data and plotting possible values of data collected and analyzed Variables are characteristics that vary from person to person (unit of observation) Identify variables as categorical, numerical or binary.
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Graphical representation of a distribution The distribution of a variable tells us what values it takes and how often it takes these values. We are looking for a different model. Multivariable – places a person in one of several categories or categories. Numerical variables – taking on numerical values whose numerical operations make sense Distributive variables – what values does it take and how often, .
In August 2005, researchers from the American Society for Microbiology and the Soap and Detergent Association monitored the behavior of more than 6,300 users of public restrooms. They have seen people in public places like Turner Field in Atlanta and Grand Central Station in New York. They found that 2393 out of 3206 men washed their hands, while 2802 out of 3130 women. What is the proportion of men who wash their hands? What proportion of women wash their hands? Do these agree with the following bar charts? Comment on what your calculations and bar graph show about which gender is more likely to wash their hands after using public toilets. In each city, estimate the number of people who washed their hands as accurately as possible on the graph. Atlanta: Chicago: New York: San Francisco: Comment on what the bar graphs show how these cities compare when it comes to hand washing.
Study people who wash their hands after using the toilet We can look at the % of all data collected whether they wash their hands or not. Each region washes its hands
The National Highway Traffic Safety Administration (NHTSA) lists the percentage of residents in each state who regularly wear seat belts as well as whether the state has a mandatory seat belt law. The primary law means that drivers can only be stopped for using a seat belt, while the secondary law means that a driver can only be stopped for another reason. The 2005 data appear in the following table (top, p primary and * undetermined): What are the units of observation for this data? Classify each of the variables in the table as either a category (also binary) or a number. What do you think is the percentage of common use in a state with a basic type seat belt law? What about a state with a second type of law? (Do not do any calculations; base your answers on the informal reading of the dotted areas.) Primary: Secondary: Does a primary law state always have a higher percentage of use than a state with secondary? Explain. If not, identify several states where primary jurisdiction is subject to the use of the second percent of the law. Do states with primary legislation tend to benefit at a higher percentage than states with secondary legislation? Explain how you can classify the score points. Does the data seem to support the claim that strict (primary) laws lead to increased seat belt use? Can you draw this conclusion realistically? Explain.
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What type of variable? Create a DOTPLOT visualization, a useful way to display a small collection of numerical variables. Mark the axis, especially if there is more than one group. two groups or quantitative changes – compared to 2 or more groups or data analysis Use words like change, average, lead to show the results.
12 Note and a summary chart Bar or points are generally highlighted when we compare the distribution of variables between two or more Statistical trends – when we compare 2 or more groups or analyze a collection of data . But this is not a complete rule for the variables of division and quantity. Be careful with your language. This is also true for cause and effect conclusions. Label your graphs Attention, when asked for ratio (0-1) or percentage (0% – 100%) Histograms are easier to compare than raw data. Always link your comments to the context of the data and as relevant to the question of interest.
Consistency refers to the range or spread of values in a data set for a quantitative variable. When describing a distribution, refer to both the center (variation) and the spread (constancy).
The data provides insight into interesting questions. Generalize the results of the study on a larger group than you used in the study itself. Population – the study refers to the entire group of people or objects (unit of observation) of interest Sample – usually a small part of the population from which data is collected to learn more about people. If the sample is carefully selected (representative of the population), you can learn more about the population. Sample size – the number of observation units (people or objects) studied in a sample. Sampling bias – sampling methods tend to systematically over-represent some parts of the population and under-represent others.
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Convenience sampling – a sample chosen for convenience of acquisition. Voluntary response – a sample selected so that members of the public can decide for themselves whether or not to participate in the study. Non-response – the problem arises when the observation group does not respond to the study Sampling pattern – the list used to select the subjects does not represent all the differences in the population – the number that defines the population (P-P) Demographic – the number that defines the sample (P-P). S-S)
17 Movement 3-1 page 34 Elvis Presley is reported to have died at his Graceland home on August 16. On the 12th anniversary of this event, a Dallas record company wanted to know the opinion of all American adults. about the issue to find out if Elvis really died. . But of course, they couldn’t ask that question to all American adults, so they sponsored a nationwide telephone survey. Listeners to more than 100 radio stations were asked to call a number (at a cost of $2.50) to give their opinion on Elvis’ actual death. It turns out that 56% of the callers thought that Elvis was alive. This phenomenon is very common in statistics: you want to know more about a large group based on data from a small group.
18 Activity 3-1 page 34 (continued) In 1936, Literary Digest magazine conducted a public opinion poll (to this day) of history. They sent questionnaires to more than 10 million people whose names and addresses were obtained from telephone directories and automobile listings. More than 2.4 million people responded, with 57% saying they would vote for Republican Alf Landon in the next presidential election. (Democrat Franklin Roosevelt won the right-wing election, with 63% of the popular vote.)
Explanatory Variable – The variable whose effect you want to study. Response variable – The variable you are suspecting
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