# data[].attributes.headline
What I have learned so far is that the same data can be used to present a different points of view.

# data[].attributes.subject
What I have learned so far is that the same data can be used to present a different points of view.

# data[].attributes.headline
i want to know how to make the box and whisker plot on word 

# data[].attributes.subject
i want to know how to make the box and whisker plot on word 

# data[].attributes.headline
I learned how to find the quartiles and the interquartiles. This lesson refreshed my memory on what I thought I didn't know. 

# data[].attributes.subject
I learned how to find the quartiles and the interquartiles. This lesson refreshed my memory on what I thought I didn't know. 

# data[].attributes.body
I would like to know how to make box and whisker plots in word/powerpoint without having to scan in a document.

# data[].attributes.headline
Do we just dispose the outliers when it comes to drawing box plots. 

# data[].attributes.subject
Do we just dispose the outliers when it comes to drawing box plots. 

# data[].attributes.headline
what i would like to know is when to use and when to not use some charts.

# data[].attributes.subject
what i would like to know is when to use and when to not use some charts.

# data[].attributes.headline
What I want to get better at or learn more about is how to reverse solve for the mean. Such as being given an already established mean and determine what is needed to change it. Like we have been practicing. 

# data[].attributes.subject
What I want to get better at or learn more about is how to reverse solve for the mean. Such as being given an already established mean and determine what is needed to change it. Like we have been practicing. 

# data[].attributes.headline
I would like to know more about how statistics can be manipulated or skewed, or be misleading.

# data[].attributes.subject
I would like to know more about how statistics can be manipulated or skewed, or be misleading.

# data[].attributes.body
How simple it is to create a box and whiskers chart

# data[].attributes.headline
I knew how to draw a box and whisker plot.

# data[].attributes.subject
I knew how to draw a box and whisker plot.

# data[].attributes.body
What I learned is that there is more to the basics of box and whiskers plot. I need to refresh all these terms i.e. quartile, median, outlier more.

# data[].attributes.headline
How to read and understand data. How to read data to get the clearest and most accurate information on what is being presented. 

# data[].attributes.subject
How to read and understand data. How to read data to get the clearest and most accurate information on what is being presented. 

# data[].attributes.body
I would like to know how to use the sigma and mu symbols

# data[].attributes.headline
I have relearned how to create a box and whisker plot and how to find the outliers.

# data[].attributes.subject
I have relearned how to create a box and whisker plot and how to find the outliers.

# data[].attributes.body
want to know all the basics of stem and leaf plot. Need more practice. Need to know how to figure the 5th quiz

# data[].attributes.headline
What I already know about MCT is the very basics such as mean median mode and all the points used to plot a box and whisker graph. 

# data[].attributes.subject
What I already know about MCT is the very basics such as mean median mode and all the points used to plot a box and whisker graph. 

# data[].attributes.body
IQR

# data[].attributes.headline
I know how to find the mean median and mode. I also a m familiar with the box and whisker plot 

# data[].attributes.subject
I know how to find the mean median and mode. I also a m familiar with the box and whisker plot 

# data[].attributes.headline
I relearned what makes up a box and whisker plot. 

# data[].attributes.subject
I relearned what makes up a box and whisker plot. 

# data[].attributes.headline
I learned how to calculate the charts and how they can be used in real world situations.

# data[].attributes.subject
I learned how to calculate the charts and how they can be used in real world situations.

# data[].attributes.body
I learned how to find outliers on a box and whisker plot

# data[].attributes.body
How to make a box and whisker plot on word.

# data[].attributes.body
I am least familiar with quartiles. And how to compute them

# data[].attributes.headline
I know how to calculate mean, median and mode.

# data[].attributes.subject
I know how to calculate mean, median and mode.

# data[].attributes.body
I have learned (or rather had a refresher) about box and whiskers plots and stem and leaf plots. I also remember how to find the interquartile range. I learned how to find outliers in the box and whisker plots.

# data[].attributes.body
How measures can be used to skew data / how to ID data that has been skewed by using the wrong MCT

# data[].attributes.body
What I learned is that there is more levels to it from what I can remember.

# data[].attributes.headline
I Know that the measures of central tendency is about finding a central value of multiple numbers.

# data[].attributes.subject
I Know that the measures of central tendency is about finding a central value of multiple numbers.

# data[].attributes.body
I know how to calculate the mean, median, and mode for a set of numbers

# data[].attributes.headline
I understand the basics of mean, median, mode and range. 

# data[].attributes.subject
I understand the basics of mean, median, mode and range. 

# data[].attributes.body
I can find the mean median and mode.

# data[].attributes.headline
I knew the terms and what some of them meant.

# data[].attributes.subject
I knew the terms and what some of them meant.

# data[].attributes.body
The general terms and their meanings only. Mean median mode

# data[].attributes.body
What I want to know is how to take it to the next level when it comes to finding the mean sometimes. Like the question is participation 2.

# data[].attributes.body
I am familiar with mean ,median and mode .

# data[].attributes.body
I know the basics of mean, median, mode, and range.

# data[].attributes.body
What I know Is all the basics.