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Gathering information about an entire population often costs too much or is virtually impossible. Instead, we use a sample of the population. A sample should have the same characteristics as the population it is representing. Most statisticians use various methods of random sampling in an attempt to achieve this goal.
So one way to assess whether our population follows a normal distribution model is to construct a histogram from our sample data and visually determine whether it "looks normal," that is, approximately symmetric and bell-shaped.
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- Populations
- Population vs Sample
- Subpopulations Can Improve Your Analysis
- Parameter vs Statistic
- Representative Sampling and Simple Random Samples
- Example of A Population with Important Subpopulations
Populations can include people, but other examples include objects, events, businesses, and so on. In statistics, there are two general types of populations. Populations can be the complete set of all similar items that exist. For example, the population of a country includes all people currently within that country. It’s a finite but potentially l...
It’s virtually impossible to measure a whole population completely because they tend to be extremely large. Consequently, researchers must measure a subset of the population for their study. These subsets are known as samples. Typically, a researcher’s goal is to draw a representative sample from their target population. A representative sample mir...
Subpopulations share additional attributes. For instance, the population of the United States contains the subpopulations of men and women. You can also subdivide it in other ways such as region, age, socioeconomic status, and so on. Different studies that involve the same population can divide it into different subpopulations depending on what mak...
A parameter is a value that describes a characteristic of an entire population, such as the population mean. Because you can almost never measure an entire population, you usually don’t know the real value of a parameter. In fact, parameter values are nearly always unknowable. While we don’t know the value, it definitely exists. For example, the av...
In statistics, sampling refers to selecting a subset of a population. After drawing the sample, you measure one or more characteristics of all items in the sample, such as height, income, temperature, opinion, etc. If you want to draw conclusions about these characteristics in the whole population, it imposes restrictions on how you collect the sam...
Suppose we’re studying the height of American citizens and let’s further assume that we don’t know much about the subject. Consequently, we collect a random sample, measure the heights in centimeters, and calculate the sample mean and standard deviation. Here is the CSV data file: Heights. We obtain the following results: Because we gathered a rand...
In the chart, we see the global population growth rate per year. This is based on historical UN estimates and its medium projection to 2100. Global population growth peaked in the 1960s at over 2% per year.
- Pareto Diagram or Bar Graph. A Pareto diagram or bar graph is a way to visually represent qualitative data. Data is displayed either horizontally or vertically and allows viewers to compare items, such as amounts, characteristics, times, and frequency.
- Pie Chart or Circle Graph. Another common way to represent data graphically is a pie chart. It gets its name from the way it looks, just like a circular pie that has been cut into several slices.
- Histogram. A histogram in another kind of graph that uses bars in its display. This type of graph is used with quantitative data. Ranges of values, called classes, are listed at the bottom, and the classes with greater frequencies have taller bars.
- Stem and Leaf Plot. A stem and leaf plot breaks each value of a quantitative data set into two pieces: a stem, typically for the highest place value, and a leaf for the other place values.
Dec 29, 2022 · Example 1. Solution. Definition: Parameter. Definition: Census. Definition: Sample. Definition: Statistic. Example 2. Solution.
