When scientists draw random samples to be measured they expect their results will be accurate, assuming all systematic errors have been removed from the experiment. Unlike systematic errors, random errors cannot be removed from the experiment – only reduced. If several replicates are measured for each sample, random errors are mathematically minimized and are relegated to affecting precision, not accuracy. For some students, the difference between accuracy and precision is not clear enough for this to make sense. The solution is for students to interact with the statistics, which requires the laborious generation of multiple sets of random numbers, numerical comparisons, and graphical presentations of the data. The purpose of the spreadshee...
Using a simulation approach, and with collaboration among peers, this paper is intended to improve t...
This article examined the tradeoff between data analysis and simulations in the learning of statisti...
People often extrapolate from data samples, inferring properties of the population like the rate of ...
When scientists draw random samples to be measured they expect their results will be accurate, assum...
Sampling error refers to variability that is unique to the sample. If the sample is the entire popul...
Data have become extremely important in the world today. Information is everywhere, and people are w...
International audienceIncluding a 'frequentist' point of view has resulted in experimentation becomi...
A poor understanding of statistical analysis has been proposed as a key reason for lack of replicabi...
Drawing statistical inferences (SI) is essential in a society where data are of increasing importanc...
Mathematical Statistics describes the mathematical underpinnings associated with the practice of sta...
As an extension to an activity introducing Year 5 students to the practice of statistics, the softwa...
One of the greatest difficulties in teaching statistics is imparting an understanding of the procedu...
International audienceDrawing statistical inferences (SI) is essential in a society where data are o...
In various surveys, presence of measurement errors has led to misleading results in estimation of va...
<p><b>a.</b><i>Sampling multiplier vs fidelity</i>. The sampling multiplier, magnitude above the siz...
Using a simulation approach, and with collaboration among peers, this paper is intended to improve t...
This article examined the tradeoff between data analysis and simulations in the learning of statisti...
People often extrapolate from data samples, inferring properties of the population like the rate of ...
When scientists draw random samples to be measured they expect their results will be accurate, assum...
Sampling error refers to variability that is unique to the sample. If the sample is the entire popul...
Data have become extremely important in the world today. Information is everywhere, and people are w...
International audienceIncluding a 'frequentist' point of view has resulted in experimentation becomi...
A poor understanding of statistical analysis has been proposed as a key reason for lack of replicabi...
Drawing statistical inferences (SI) is essential in a society where data are of increasing importanc...
Mathematical Statistics describes the mathematical underpinnings associated with the practice of sta...
As an extension to an activity introducing Year 5 students to the practice of statistics, the softwa...
One of the greatest difficulties in teaching statistics is imparting an understanding of the procedu...
International audienceDrawing statistical inferences (SI) is essential in a society where data are o...
In various surveys, presence of measurement errors has led to misleading results in estimation of va...
<p><b>a.</b><i>Sampling multiplier vs fidelity</i>. The sampling multiplier, magnitude above the siz...
Using a simulation approach, and with collaboration among peers, this paper is intended to improve t...
This article examined the tradeoff between data analysis and simulations in the learning of statisti...
People often extrapolate from data samples, inferring properties of the population like the rate of ...