Thank you for this video! My professor read from a power point slide and didn't break it down the way you did. I learned more through this video then from a week's worth of class.
question, sir. i noticed the actual figures have negative values. shouldn't be values always positive? because shouldn't it be that the values when plotted on a graph should form a trend line and that they should be positive. this is what i am thinking because the trend line is plotted on the positive quadrant of the graph. thanks.
I gather this is a complicated version of "find the slope given 2 points": (y2-y1)/(x2-x1) sum(xy) - sum(x)* avg(y) is the equivalent of (y2-y1)....... sum(X squared) - count(x)*avg(x) squared is the equivalent of (x2-x1) Why this is so can it be explained in words?
I really appreciate you taking the time to explain this! I was curious, is there a reason the actual's are treated as all being positive numbers even though most (but not all) are wrote as negatives? Or am I mistaking the parentheses for projections? Thanks again!
The parentheses are a way of saying: when the numbers become available - to extend into the future. At the end of the month when the actual numbers become available. Does that help? Thanks for watching.
Hi Nicholas, You are correct, that in account the parentheses (32) indicate a negative number. The parenthesis have a different meaning in operations, they stand for “when the information comes available”. In this case the parenthesis stand for when the actual forecast becomes available at the end of the month. This is a teaching tool that allows for practice without re-writing the problem many times. Thanks for watching, Ed
261.1 - 35.37(5.5)= 261.1 - 194.5 = 66.5, maybe it is the scientific notation that is confusing? 35.37(5.5) is the same as 35.37 * 5.5. Enjoy my friend.
I am missing something, please help me out. I do my calculations using Excel so sometimes the round off error is a few decimal points when I do it on the board. With Excel the 261.1 subtract the product of 35.7 multiplied by 5.5 equals 66.5. 261.1 - 194.535 = 66.565. Enjoy my friend and thanks for the comment.
For linearity, one of the assumptions is a linear trend. Typically, we would look at a scatter plot of the data to observe a trend before forecasting. There are several statistical procedures that may be run to check for normality of variance. Non-linear trends are usually explored with qualitative techniques to explain the phenomena.
I'm dancing right now in my chair taking an online test. Thank you for the help
Thank you for this video! My professor read from a power point slide and didn't break it down the way you did. I learned more through this video then from a week's worth of class.
The best and most clear educational video I ever came across! Thank you so much!
Thank you, Aliona.
Hello, thank you very much for this clear, detailed and straight forward explanation.
Enjoy.
finally!!!!! best way to explain this. Thank you!!!
Thanks a lot man , that was clear and it helped me out a lot
Thanks for watching.
Watching this in 2020! It was very clear and very helpful. Thanks a lot :-)
Thank you
Thank you for your help. You helped me a lot! Best wishes from Mexico.
THANK GOODNESS for this video.
excellent video
Thank you for watching.
Thank you very much, sir.
Wow, is there anything more boring than someone reading from a power point? Thanks for watching.
I love you! Thank u so much!
great video! thanks for the help
Still relevant in 2021 Statistics 3001
question, sir. i noticed the actual figures have negative values. shouldn't be values always positive? because shouldn't it be that the values when plotted on a graph should form a trend line and that they should be positive. this is what i am thinking because the trend line is plotted on the positive quadrant of the graph. thanks.
The trend line can be either. If trend is increasing then positive, if trend is decreasing then negative. Thanks for watching.
Thnx for ur help
Thanks.
nice lecture
I gather this is a complicated version of "find the slope given 2 points": (y2-y1)/(x2-x1)
sum(xy) - sum(x)* avg(y) is the equivalent of (y2-y1).......
sum(X squared) - count(x)*avg(x) squared is the equivalent of (x2-x1)
Why this is so can it be explained in words?
I really appreciate you taking the time to explain this! I was curious, is there a reason the actual's are treated as all being positive numbers even though most (but not all) are wrote as negatives? Or am I mistaking the parentheses for projections? Thanks again!
The parentheses are a way of saying: when the numbers become available - to extend into the future. At the end of the month when the actual numbers become available. Does that help? Thanks for watching.
Hi Nicholas, You are correct, that in account the parentheses (32) indicate a negative number. The parenthesis have a different meaning in operations, they stand for “when the information comes available”. In this case the parenthesis stand for when the actual forecast becomes available at the end of the month. This is a teaching tool that allows for practice without re-writing the problem many times. Thanks for watching, Ed
thaaaaaanks a lot u ve saved my life !
What is the name of this method?
Linear Trend, which is part of my Forecasting module.
What we are given years on the x axis
How does 261.1 - 35.37 (5.5) gives us 66.5?
261.1 - 35.37(5.5)= 261.1 - 194.5 = 66.5, maybe it is the scientific notation that is confusing? 35.37(5.5) is the same as 35.37 * 5.5. Enjoy my friend.
I am missing something, please help me out. I do my calculations using Excel so sometimes the round off error is a few decimal points when I do it on the board. With Excel the 261.1 subtract the product of 35.7 multiplied by 5.5 equals 66.5. 261.1 - 194.535 = 66.565. Enjoy my friend and thanks for the comment.
Sir what if we are given years on the y axis
What about non-linear trends ?
For linearity, one of the assumptions is a linear trend. Typically, we would look at a scatter plot of the data to observe a trend before forecasting. There are several statistical procedures that may be run to check for normality of variance. Non-linear trends are usually explored with qualitative techniques to explain the phenomena.