0
In statistics what would you call the conclusions drawn about a population?
Wiki User
∙ 16y ago
INFERENCES
Any calculated number from a sample from the population is called a 'statistic', such as the mean or the variance.
Wiki User
∙ 16y ago
Add your answer:
Earn +20 pts
How do inferential statistics describe data differently than descriptive statistics?
The term "descriptive statistics" generally refers to such information as the mean (average), median (midpoint), mode (most frequently occurring value), standard deviation, highest value, lowest value, range, and etc. of a given data set. It is a loosely used term, and not always meant to contrast with inferential statistics as the question implies. But in the context of the question, descriptive statistics would be information that pertains only to the data that has actually been collected. In the case of an instructor calculating an average grade for a class, for example, the collected data would most likely be the only point of interest. Thus, descriptive statistics would be enough. However, it is more common for a researcher to use a sample of collected data to make inferences and draw conclusions about a larger group (or "population") that the sample represents. For example, if you wanted to know the average age of users of this site, it would be unrealistic to question every singe user. So you might question a small sample and then extend that information to all users. But if you found the average age in your sample to be 40, you could not immediately assume that 40 is the average for all users. You would need to use inferential statistics to calculate an estimate of how accurately your data represents the larger group. The most common way to do this is to calculate a standard error, which will produce a range within which the population average most likely (but not definitively) lies. Therefore, in the simplest description (inferential statistics are also a part of much more powerful tests outside of this answer), descriptive statistics refer only to a sample while inferential statistics refer to the larger population from which the sample was drawn.
Does descriptive statistics means parametric statistics?
No. Descriptive statistics are those that characterise samples without attempting to draw conclusions. The purpose of them is to help investigators to form an understanding of what the data might be capable of telling them. Descriptive statistics include graphs as well as measures of location, scale, correlation, and so on. Parametric statistics are those that are based on probabilistic models (ie, mathematical models involving probability) that involve parameters. For instance, an investigator might assume that her results have come from a population that is normally distributed with a certain mean and standard deviation; this would be a parametric model. She could estimate this pair of parameters, the mean and standard deviation, using parametric statistics, or test hypotheses about them, again using parametric statistics. In either case the parametric statistics she uses would be based on the parametric mathematical model she has chosen for her data.
What the difference between statistic as numerical fact and statistics as a discipline?
A statistic (as a numerical fact) is a value taken from a sample of a population. For example a summary of a political poll would produce many numerical statistics. Statistics as a discipline involves creating and carrying out sampling designs, knowing how to analyze data, creating mathematical models for different processes, predicting future results, and optimizing systems. That is why statistics can by applied to any other field of study, any time you have to research, prove, or improve something the discipline of statistics is very valuable.
How can statistics be applied in payroll?
Statistics are applied to payroll in many different ways. The determination of the unemployment rate is found by applying payroll statistics. Without applying statistics to payroll the unemployment rate would not be found.
What are the uses of statistics?
Statistics is primarily used either to make predictions based on the data available or to make conclusions about a population of interest when only sample data is available. In both cases statistics tries to make sense of the uncertainty in the available data. When making predictions statisticians determine if the difference in the data points are due to chance or if there is a systematic relationship. The more the systematic relationship that is observed the better the prediction a statistician can make. The more random error that is observed the more uncertain the prediction. Statisticians can provide a measure of the uncertainty to the prediction. When making inference about a population, the statistician is trying to estimate how good a summary statistic of a sample really is at estimating a population statistic. For example, a statistician may be asked to estimate the proportion of women who smoke in the US. This is a population statistic. The only data however may be a random sample of 1000 women. By estimating the proportion of women who smoke in the random sample of 1000, a statistician can determine how likely the sample proportion is close to the population proportion. A statistician would report the sample proportion and an interval around that sample proportion. The interval would indicate with 95% or 99% certainty that the population proportion is within that interval, assuming the sample is really random. School Grades, medical fields when determining whether something works, and marketing works
What is the conclusion of grass?
There are quite a few conclusions that can be drawn about the grasshopper. Many would conclude that he is lazy.
Iwhat does in statistics what does population mean n statistics?
I believe this question is asking what a population is in statistics. A "population" is simply the group from which a sample is drawn to conduct statistics. It is often wrongly assumed that "population" refers to all people, at least in the social sciences, or all of whatever the research is studying in other fields. For example, suppose you wanted to know the average length of time that teenagers watch television. You would obviously not be able to ask every teenager. So you would collect data from a random sample of teenagers. Thus, your population would be teenagers. However, some caution is necessary. If you collected only from teenagers in the United States, you could not really say that your population is all teenagers in the world. You would probably describe the population as US teenagers. In this case, then, a responsible researchers should make an effort to collect data from different states. Expanding this, you can see how the issue becomes difficult. Some researchers maintain that if you collect only data from say, sophomores at one university (more common than you think), your population can only be all sophomores at that university. Other researchers are more liberal in expanding the definition of the population, and the debate is ongoing. What is important, however, is that the sample reasonably reflects the population. Thus, the boundaries of the population are rarely so wide as to include "all" or "every" of anything. But they must still be wide enough that the research has some importance beyond just the sample, which is the ultimate goal of both science and statistics. Where the line is drawn is often a decision that you have to make and justify yourself in your project.
Would not be included in a description of technology?
it is most closely related to the process of examining population statistics
What are the problems of missing frequencies in a frequency table in statistics?
Conclusions based on missing frequencies are likely to be seriously flawed. However, if the data follow a known distribution, it may be possible to get some indication of the likely values for the missing frequencies. Nevertheless, this would weaken any conclusions.
How do inferential statistics describe data differently than descriptive statistics?
The term "descriptive statistics" generally refers to such information as the mean (average), median (midpoint), mode (most frequently occurring value), standard deviation, highest value, lowest value, range, and etc. of a given data set. It is a loosely used term, and not always meant to contrast with inferential statistics as the question implies. But in the context of the question, descriptive statistics would be information that pertains only to the data that has actually been collected. In the case of an instructor calculating an average grade for a class, for example, the collected data would most likely be the only point of interest. Thus, descriptive statistics would be enough. However, it is more common for a researcher to use a sample of collected data to make inferences and draw conclusions about a larger group (or "population") that the sample represents. For example, if you wanted to know the average age of users of this site, it would be unrealistic to question every singe user. So you might question a small sample and then extend that information to all users. But if you found the average age in your sample to be 40, you could not immediately assume that 40 is the average for all users. You would need to use inferential statistics to calculate an estimate of how accurately your data represents the larger group. The most common way to do this is to calculate a standard error, which will produce a range within which the population average most likely (but not definitively) lies. Therefore, in the simplest description (inferential statistics are also a part of much more powerful tests outside of this answer), descriptive statistics refer only to a sample while inferential statistics refer to the larger population from which the sample was drawn.
How many Filipinos in 2008?
The National Statistics Office projected that the Philippine population would be 90,457,200 in 2008.
Does descriptive statistics means parametric statistics?
No. Descriptive statistics are those that characterise samples without attempting to draw conclusions. The purpose of them is to help investigators to form an understanding of what the data might be capable of telling them. Descriptive statistics include graphs as well as measures of location, scale, correlation, and so on. Parametric statistics are those that are based on probabilistic models (ie, mathematical models involving probability) that involve parameters. For instance, an investigator might assume that her results have come from a population that is normally distributed with a certain mean and standard deviation; this would be a parametric model. She could estimate this pair of parameters, the mean and standard deviation, using parametric statistics, or test hypotheses about them, again using parametric statistics. In either case the parametric statistics she uses would be based on the parametric mathematical model she has chosen for her data.
What is the population of Maerdy?
As of my available data, I couldn't determine the population of Maerdy. It would be best to refer to the latest official statistics or census data to get accurate population information.
What are the Conclusions about Journalism?
The conclusions would be a summary of whatever you have discovered in relation to the subject.
What is sampling in maths?
In statistics, sampling is a process of collecting information from a subset of a population so as to reach conclusions about the whole population. This method is used because collecting information from the whole population is likely to be expensive and time consuming, and in some cases pointless. For example, if you tested the life expectancy of all light bulbs, you would have none left to sell!
Were soviets soldiers workers?
The Soviet Union had a standing professional army drawn from the population of the country. they had conscription and in times of war drew forces from the general population. so it would have been a mixture of professional soldiers and conscript drawn from schools and the work force.
What conclusion can be drawn from the fact that no part of Ireland is more than 20 miles from the sea?
Lots of parts of Ireland are more than 20 miles from the sea. Nowhere would be more than about 80 or 90 miles from the sea. The conclusions that can be drawn is that Ireland is not very large compared to some countries.
