What is the entire collection of individuals about which information is sought?
Midterm
| Question | Answer |
|---|---|
| The entire collection of individuals about which information is being sought is called a _____ | population |
| A ____ sample is one in which the population is divided into groups and a random sample of groups is drawn. | cluster |
What do you call a number that describes sample characteristics?
A statistic is a numerical measurement describing some characteristic of a sample.
Is a sample chosen by a method in which each collection of items of the same size from the population is equally likely to make up the sample?
of size n is a sample chosen by a method in which each collection of n population items is equally likely to comprise the sample. It is analogous to the lottery. In cluster sampling, items are drawn from the population in groups.
What are variables that classify individuals into categories?
Qualitative variables, also called categorical variables, classify individuals into categories. For example, college major and gender are qualitative variables.
What is the sampling process?
Sampling is a process used in statistical analysis in which a predetermined number of observations are taken from a larger population. The methodology used to sample from a larger population depends on the type of analysis being performed, but it may include simple random sampling or systematic sampling.
What are the main elements of sampling?
Main elements of sampling : Following are main elements (essentials) of sampling:
- A sample is the representative of all the characters of universe.
- All units of sample must be independent of each other.
- The number of items in the sample should be fairly adequate.
What is the purpose of sampling?
The primary goal of sampling is to get a representative sample, or a small collection of units or cases from a much larger collection or population, such that the researcher can study the smaller group and produce accurate generalizations about the larger group.
What is the importance of sampling?
Sampling saves money by allowing researchers to gather the same answers from a sample that they would receive from the population. Non-random sampling is significantly cheaper than random sampling, because it lowers the cost associated with finding people and collecting data from them.
What are the advantages and disadvantages of sampling?
Advantages and Disadvantages of Sampling
- Low cost of sampling.
- Less time consuming in sampling.
- Scope of sampling is high.
- Accuracy of data is high.
- Organization of convenience.
- Intensive and exhaustive data.
- Suitable in limited resources.
- Better rapport.
What is the difference between mean and sample mean?
Differences. “Mean” usually refers to the population mean. This is the mean of the entire population of a set. The mean of the sample group is called the sample mean.
What is another word for sample?
Some common synonyms of sample are case, example, illustration, instance, and specimen.
What is the characteristics of sample?
The Main Characteristics of Sampling In sampling, we assume that samples are drawn from the population and sample means and population means are equal. A population can be defined as a whole that includes all items and characteristics of the research taken into study.
What is a biased sample?
Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others. It is also called ascertainment bias in medical fields. Sampling bias limits the generalizability of findings because it is a threat to external validity, specifically population validity.
How do you explain simple random sampling?
Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population. Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.
Why do we use simple random sampling?
Simple random sampling is a method used to cull a smaller sample size from a larger population and use it to research and make generalizations about the larger group. The advantages of a simple random sample include its ease of use and its accurate representation of the larger population.