Yes--these two terms mean essentially the same thing. There might be variation among practicing statisticians and researchers (perhaps geographically, with those in the U.S. preferring the phrase "inferential" and those in other countries perhaps more likely to use "inductive"). The goal of inferential statistics is to make a broader statement about a large group from a small subset of that group--and the phrase "inductive reasoning" refers to making a broader generalization (that is, an inference) from a series of observations. Thus, these two phrases refer to the same thing.
There is no inferential data. There is inferential statistics which from samples, you infer or draw a conclusion about the population. Hypothesis testing is an example of inferential statistics.
Inferential statistics uses data from a small group to make generalizations or inferences about a larger group of people. Inferential statistics should be used with "inferences".
Descriptive statistics is a summary of data. Inferential statistics try to reach conclusion that extend beyond the immediate data alone.
One advantage of inferential statistics is that large predictions can be made from small data sets. However, if the sample is not representative of the population then the predictions will be incorrect.
The two main forms of statistics are qualitative (descriptive) statistics and quantitative (inferential or inductive) statistics.
Yes--these two terms mean essentially the same thing. There might be variation among practicing statisticians and researchers (perhaps geographically, with those in the U.S. preferring the phrase "inferential" and those in other countries perhaps more likely to use "inductive"). The goal of inferential statistics is to make a broader statement about a large group from a small subset of that group--and the phrase "inductive reasoning" refers to making a broader generalization (that is, an inference) from a series of observations. Thus, these two phrases refer to the same thing.
There is no inferential data. There is inferential statistics which from samples, you infer or draw a conclusion about the population. Hypothesis testing is an example of inferential statistics.
Descriptive statistics describe the main features of a collection of data quantitatively. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a data set quantitatively without employing a probabilistic formulation, rather than use the data to make inferences about the population that the data are thought to represent.
Why are measures of variability essential to inferential statistics?
Yes. Descriptive statistics are methods of organizing, summarizing, and presenting data in an informative way. Inferential Statistics (also called statistical inference) the methods used to estimate a property of a population on the basis of a sample.
Inferential statistics uses data from a small group to make generalizations or inferences about a larger group of people. Inferential statistics should be used with "inferences".
Descriptive statistics is a summary of data. Inferential statistics try to reach conclusion that extend beyond the immediate data alone.
There are two types of statistics. One is called descriptive statistics and the other is inferential statistics. Descriptive statistics is when you use numbers. Inferential statistics is when you draw conclusions or make predictions.
Descriptive and Inferential Statistics
One advantage of inferential statistics is that large predictions can be made from small data sets. However, if the sample is not representative of the population then the predictions will be incorrect.
Descriptive statistics are meant to describe the situation such as the average or the range. Inferential statistics is used to differentiate between a couple of groups.