Exploring the Various Definitions in Statistics
Statistics definitions
Bias-Bias is a term which refers to how far the average statistic lies from the parameter it is estimating, that is, the error which arises when estimating a quantity. Errors from chance will cancel each other out in the long run, those from bias will not.
Primary data-Data observed or collected directly from first-hand experience.
Secondary data-Published data and the data collected in the past or other parties
Qualitative data-Qualitative methods are ways of collecting data which are concerned with describing meaning, rather than with drawing statistical inferences. What qualitative methods (e.g. case studies and interviews) lose on reliability they gain in terms of validity. They provide a more in depth and rich description.
Quantitive data-Quantitative methods have come under considerable criticism. In modern research, most psychologists tend to adopt a combination of qualitative and quantitative approaches, which allow statistically reliable information obtained from numerical measurement to be backed up by and enriched by information about the research participants' explanations
Discrete data-This is called discrete data because the units of measurement (for example, CDs) cannot be split up; there is nothing between 1 CD and 2 CDs.
Continuous data-This data is called continuous because the scale of measurement - distance - has meaning at all points between the numbers given, eg we can travel a distance of 1.2 and 1.85 and even 1.632 miles.
Continuous data can be shown on a number line, and all points on the line have meaning and are different, but with discrete data only certain values have meaning
Categorical data-A set of data is said to be categorical if the values or observations belonging to it can be sorted according to category. Each value is chosen from a set of non-overlapping categories. For example, shoes in a cupboard can be sorted according to colour: the characteristic 'colour' can have non-overlapping
Bias-Bias is a term which refers to how far the average statistic lies from the parameter it is estimating, that is, the error which arises when estimating a quantity. Errors from chance will cancel each other out in the long run, those from bias will not.
Primary data-Data observed or collected directly from first-hand experience.
Secondary data-Published data and the data collected in the past or other parties
Qualitative data-Qualitative methods are ways of collecting data which are concerned with describing meaning, rather than with drawing statistical inferences. What qualitative methods (e.g. case studies and interviews) lose on reliability they gain in terms of validity. They provide a more in depth and rich description.
Quantitive data-Quantitative methods have come under considerable criticism. In modern research, most psychologists tend to adopt a combination of qualitative and quantitative approaches, which allow statistically reliable information obtained from numerical measurement to be backed up by and enriched by information about the research participants' explanations
Discrete data-This is called discrete data because the units of measurement (for example, CDs) cannot be split up; there is nothing between 1 CD and 2 CDs.
Continuous data-This data is called continuous because the scale of measurement - distance - has meaning at all points between the numbers given, eg we can travel a distance of 1.2 and 1.85 and even 1.632 miles.
Continuous data can be shown on a number line, and all points on the line have meaning and are different, but with discrete data only certain values have meaning
Categorical data-A set of data is said to be categorical if the values or observations belonging to it can be sorted according to category. Each value is chosen from a set of non-overlapping categories. For example, shoes in a cupboard can be sorted according to colour: the characteristic 'colour' can have non-overlapping