Fkkkkkkk
Key Points
Measurement issues
Chance
P value
Confidence intervals
Measurement Bias and Error in Study Design Bias
Selection bias
Measurement bias
Confounding
Estimation
Process of using calculated sample values to determine the probable value of a population parameter
• Point estimate
• Confidence interval estimation
Range of values that has a known probability of capturing the parameter
Chance
• From estimates in the sample population make inferences about the risk in the total population
• Random error is when the value of the sample measurement diverges – due to chance from that of the true population value.
P values
• Is the result because of chance?
• Measured by P value (statistical tests)
• P value less than 0.05 P<0.05 probability of obtaining the observed value by chance is less than 1 in 20
Selection bias
Statistical error that causes a bias in the sampling portion of an experiment. The error causes one sampling group to be selected more often than other groups included in the experiment. This may produce an inaccurate conclusion if the selection bias is not identified. For example, if an experiment only selects people of a certain race with similar characteristics and excludes any group that deviates from these elements. "The students at the University had to start their experiment over because they discovered a selection bias in the species gathered."
Read more: http://www.businessdictionary.com/definition/selection-bias.html#ixzz2Sb8IWwbJ
Selection bias is a statistical bias in which there is an error in choosing the individuals or groups to take part in a scientific study.[1] It is sometimes referred to as the selection effect. The phrase "selection bias" most often refers to the distortion of a statistical analysis, resulting from the method of collecting samples. If the selection bias is not taken into account then certain conclusions drawn may be wrong.
In epidemiology, Information bias refers to bias arising
Measurement issues
Chance
P value
Confidence intervals
Measurement Bias and Error in Study Design Bias
Selection bias
Measurement bias
Confounding
Estimation
Process of using calculated sample values to determine the probable value of a population parameter
• Point estimate
• Confidence interval estimation
Range of values that has a known probability of capturing the parameter
Chance
• From estimates in the sample population make inferences about the risk in the total population
• Random error is when the value of the sample measurement diverges – due to chance from that of the true population value.
P values
• Is the result because of chance?
• Measured by P value (statistical tests)
• P value less than 0.05 P<0.05 probability of obtaining the observed value by chance is less than 1 in 20
Selection bias
Statistical error that causes a bias in the sampling portion of an experiment. The error causes one sampling group to be selected more often than other groups included in the experiment. This may produce an inaccurate conclusion if the selection bias is not identified. For example, if an experiment only selects people of a certain race with similar characteristics and excludes any group that deviates from these elements. "The students at the University had to start their experiment over because they discovered a selection bias in the species gathered."
Read more: http://www.businessdictionary.com/definition/selection-bias.html#ixzz2Sb8IWwbJ
Selection bias is a statistical bias in which there is an error in choosing the individuals or groups to take part in a scientific study.[1] It is sometimes referred to as the selection effect. The phrase "selection bias" most often refers to the distortion of a statistical analysis, resulting from the method of collecting samples. If the selection bias is not taken into account then certain conclusions drawn may be wrong.
In epidemiology, Information bias refers to bias arising