Question

One objectiveOne objective of this course is learning how to correctly interpret statistical measures. This includes learning how to identify intentionally misleading statistics. For this week's activity create your own example of a misleading statistic. Explain the context of the data, the source of the data, the sampling method that you used (or would use) to collect the data, and the (misleading) conclusions that would be drawn from your example. Be specific in explaining how the statistic is misleading. of this course is learning how to correctly interpret statistical measures. This includes learning how to identify intentionally misleading statistics. For this week's activity create your own example of a misleading statistic. Explain the context of the data, the source of the data, the sampling method that you used (or would use) to collect the data, and the (misleading) conclusions that would be drawn from your example. Be specific in explaining how the statistic is misleading.

Answer 1

Answer:-

course is learning how to correctly interpret statistical measures:-

• A solitary proportion of some characteristic of an example (i.e, mean, middle mode).It's computed by applying a capacity to the estimations of the thing of the sample.
• Which are referred to together as an arrangement of data.Let us guess build a model that we need to discover the reasonable proportion of focal propensity from the informational index which gives.
• The financial conditions/the wage level of the populace from a country.And let us guess the information are given beneath,

Income	Population
<$4000	50
$4000-$5000	70
$5000-$6000	80
$6000-$7000	65
$7000-$8000	45
$8000->	25

• Presently, we have seen that the class of the wage level is a both sided open finished class.So that here the best proportion of focal propensity of the measurement is median.
• But, on the off chance that we compute the another two factual measure i.e, mode and uniquely mean we will delicately deceptive with the data.
• Because in open finished class we can't figure the mean in light of the fact that for two open finished classes we can't locate the mid estimations of the class as the one end is missing.
• So, employments of mean in such case is the deceptive of the insights. As the classes are open end( for 2 classes) so one can by and large consider it that most extreme number of recurrence will happen in that open finished classes.
• So it is anything but a reasonable choice so mode is definitely not an appropriate proportion of insights in such cases.Here we should utilize middle for better outcome.