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How is the term confidence interval defined?
A term used in inferential statistics which measures the probability that a population parameter will fall between two set values. The confidence can take any number of probabilities, with most common probabilities being : 95% or 99%.
Would it be descriptive or inferential statistics to say that in the year 2010 that 148 million Americans will be enrolled in an HMO?
The question was posted in 2013 and so it is quite possible that the actual numbers for 2010 were available from some study. If that was the case, then the statement would be descriptive. However, it could be based on the number of Americans employed in HMOs in an earlier year together with projections based on other measures. In that case, it would be inferential.
What is Meaning of Regression in Statistics?
It measures associations between variables.
Statistic is resistant?
Which descriptive summary measures are considered to be resistant statistics
What is the different between measures of center and measures of variability?
The answer lies in the question! The first lot measure where the centre of a distribution or observation lies while the second lot are a measure of the distance of individual observations from the centre.
A scientist measures the heights of 25 oak trees. When he finds the mean of these data which phase of inferential statistics will it repr?
Data Analysis
Can variability be negative?
The usual measures of variability cannot.
How is the term confidence interval defined?
A term used in inferential statistics which measures the probability that a population parameter will fall between two set values. The confidence can take any number of probabilities, with most common probabilities being : 95% or 99%.
Would it be descriptive or inferential statistics to say that in the year 2010 that 148 million Americans will be enrolled in an HMO?
The question was posted in 2013 and so it is quite possible that the actual numbers for 2010 were available from some study. If that was the case, then the statement would be descriptive. However, it could be based on the number of Americans employed in HMOs in an earlier year together with projections based on other measures. In that case, it would be inferential.
What is the pattern of a variability within a data set called?
The range, inter-quartile range (IQR), mean absolute deviation [from the mean], variance and standard deviation are some of the many measures of variability.
What does the multiple standard error of estimate measure?
It measures the error or variability in predicting Y.
What is the difference between descriptive and inferential?
Both descriptive and inferential statistics look at a sample from some population.The difference between descriptive and inferential statistics is in what they do with that sample:Descriptive statistics aims to summarize the sample using statistical measures, such as average, median, standard deviation etc. For example, if we look at a basketball team's game scores over a year, we can calculate the average score, variance etc. and get a description (a statistical profile) for that team.Inferential statistics aims to draw conclusions about the population from the sample at hand. For example, it may try to infer the success rate of a drug in treating high temperature, by taking a sample of patients, giving them the drug, and estimating the rate of effectiveness in the population using the rate of effectiveness in the sample.Please see the related links for more details.All statistical tests are part of Inferential analysis; there are no tests conducted in Descriptive analysis· Descriptive analysis- describes the sample's characteristics using…o Metric- ex. sample mean, standard deviation or varianceo Non-metric variables- ex. median, mode, frequencies & elaborate on zero-order relationshipso Use Excel to help determine these sample characteristics· Inferential Analysis- draws conclusions about populationo Types of errorso Issues related to null and alternate hypotheseso Steps in the Hypothesis Testing Procedureo Specific statistical tests
Why mean and standard deviation are used for inferential statistics?
The following are the two main reasons.The first is that the inference to be made is usually (but not always) about the mean or standard deviation.Many probability distribution functions (but not all) can be defined in terms of these measures so identifying them is sufficient.They are well studied and their distributions are well known, along with tests for significance.
What is Meaning of Regression in Statistics?
It measures associations between variables.
What two data characteristics are usually measured using numerical descriptive measures?
Variability and Central Tendency (Stats Student)
Statistic is resistant?
Which descriptive summary measures are considered to be resistant statistics
What are the major steps in social research?
By the time you get to the analysis of your data, most of the really difficult work has been done. It's much more difficult to: define the research problem; develop and implement a sampling plan; conceptualize, operationalize and test your measures; and develop a design structure. If you have done this work well, the analysis of the data is usually a fairly straightforward affair.In most social research the data analysis involves three major steps, done in roughly this order:Cleaning and organizing the data for analysis (Data Preparation)Describing the data (Descriptive Statistics)Testing Hypotheses and Models (Inferential Statistics)Data Preparation involves checking or logging the data in; checking the data for accuracy; entering the data into the computer; transforming the data; and developing and documenting a database structure that integrates the various measures.Descriptive Statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data. With descriptive statistics you are simply describing what is, what the data shows.Inferential Statistics investigate questions, models and hypotheses. In many cases, the conclusions from inferential statistics extend beyond the immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population thinks. Or, we use inferential statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in this study. Thus, we use inferential statistics to make inferences from our data to more general conditions; we use descriptive statistics simply to describe what's going on in our data.In most research studies, the analysis section follows these three phases of analysis. Descriptions of how the data were prepared tend to be brief and to focus on only the more unique aspects to your study, such as specific data transformations that are performed. The descriptive statistics that you actually look at can be voluminous. In most write-ups, these are carefully selected and organized into summary tables and graphs that only show the most relevant or important information. Usually, the researcher links each of the inferential analyses to specific research questions or hypotheses that were raised in the introduction, or notes any models that were tested that emerged as part of the analysis. In most analysis write-ups it's especially critical to not "miss the forest for the trees." If you present too much detail, the reader may not be able to follow the central line of the results. Often extensive analysis details are appropriately relegated to appendices, reserving only the most critical analysis summaries for the body of the report itself.
