Thank you very much for these videos since the start of yr 13 this September I’ve gone from getting B/C to almost straight A in my maths tests at school and feel much more confident about tackling questions. I wish i had known about your channel in yr12. Better late than never!
This is amazing! Well done on all your hard work - you have got so much time ahead of you, I feel sure you will continue to feel more confident and even more successful. Well done!
10:20 I’m quiet confused as to why we don’t reject null hypothesis here as I thought the value of r here is greater than the threshold to be significant
So it isn’t about it necessarily being ‘greater than’, but rather being ‘more extreme’ than the threshold. So in this case, it would be significant if r was more NEGATIVE, which actually means less than. I hope this helps!
when we have a hypothesis testing and the equation they give tells us that x is a base so its not a power to anything and the x and y are equal to logs of something else, we still use the y=a+bx to find the pmcc of the coded data right?? in a level, will we have to use any other option than y=a+bx bc i domt remember doing questions where we didnt use that option
0.609 is the observed value, and it is bigger or 'more extreme' than the value of 0.5822 from the table - this is consistent with how we did this in the previous ones! :)
Hmmm I would say strictly greater than, although the value of r that you get from the calculator will likely be a very long number, so the change of it being exactly equal are very unlikely. I wouldn’t worry too much as they shouldn’t ask anything that’s a bit undecided like this! Stats doesn’t always have an exact answer I’m afraid!
It's not so much about which is greater than or which is less than, and rather whether the r value observed is more *extreme* than the critical value. But extreme, I mean if it is MORE negative than a negative critical value, or more positive than a positive critical value. If it is more extreme than the critical value, than the strength of observed correlation is high, meaning it is significant, and so we believe there to be correlation (i.e. we reject the null hypothesis).
hello seb, i am currently cramming for paper 3 thats happening next week. any tips? also, i cant find these product momeent coefficient tables in the formula booklet, where is it?
Someone else has said where it is - towards the end of the booklet! Tips for Paper 3… I’d ask you to consider carefully which you do first, stats or mechanics, according to which you think will help you feel more comfortable quickly. Some like to do their weakest one first, others the stronger one so they have more time to look at questions they’re not sure about. Also take your time to read the Q carefully, and decide what the strategy is for the whole part of the question before starting. Good luck!
@@BicenMaths Thank you very much! I am definitely better at mechanics so I will probably start with that to get the maximum marks for it. Do you think I should spend the same amount of time for both sections?
If you think you need more time on stats, then I’d definitely jump over to it sooner than 1 hour. Might be best to do them all as quick as poss and then return at the end. Have a think what feels like it suits you best!
Because the relationship between temperature and rainfall is likely to be different for different locations in the world - eg in the UK there’s usually more rain in cold weather/winter, but maybe in other locations they have hot wet summers! So just focusing on one location will help.
@@BicenMaths Oh I see, so would focusing on one location give them a more clear trend as opposed to the one shown in the diagram? And then this would give them a better idea of the relationship between rainfall and temperature?
I’ve never seen it in an exam, but it is in the textbook - you would literally just type log(value) for each value in your calculator and then you have the values to use for the graph
Because the scientist believes that there is NO correlation - if she had said she believed there’s is negative correlation, it would be 1 tailed. Correlation just means p is not equal to 0
so even for two tailed you can just show evidence using only one tail and thats enough for the marks? if you find no correlation from one tail you dont need to check the other tail for correlation because its symmetrical so the result is the same?
Yes only investigate the tail of the end that the observed value relates to. For example, if the observed correlation is negative, only check the negative end!
Hi sir, in the previous page you said to reject h0 as r was greater than cv however in the first TTT Example you said to reject H0 even though r was smaller than the cv . I’m confused Could u please explain 😅
It's about the magnitude of the observed r vs the critical value of r. If the magnitude of the observed value is greater than the magnitude of the critical value (i.e. ignoring negatives), reject H0.
If the data is coded to linear data, and then the value of r is close to -1, then the original data is likely exponential/non-linear. The explanatory variable is the one that explains the other one - for example, temperature change often causes other things to change, so is frequently an explanatory variable.
@@BicenMaths oh I was just illiterate the question actually had non-coded data and had r close to 1 so linear regression model was suitable. But i get what u mean when they code data by taking log y and stuff. Can we say the explanatory variable is the independent variable?
So pleased you’re able to use my videos to supplement your lessons and feel confident! Keep up all the hard work, you’re clearly putting lots of time into maths, impressive stuff 👍🏼
Thank you very much for these videos since the start of yr 13 this September I’ve gone from getting B/C to almost straight A
in my maths tests at school and feel much more confident about tackling questions. I wish i had known about your channel in yr12. Better late than never!
This is amazing! Well done on all your hard work - you have got so much time ahead of you, I feel sure you will continue to feel more confident and even more successful. Well done!
Thanks for the exam questions
Thank you so much for all your videos. they are all helping me from getting out of a C to an A 🥰
You are so welcome! You're already making great progress, keep pushing on - and do let me know if you ever have any questions, always happy to help :)
10:20 I’m quiet confused as to why we don’t reject null hypothesis here as I thought the value of r here is greater than the threshold to be significant
So it isn’t about it necessarily being ‘greater than’, but rather being ‘more extreme’ than the threshold. So in this case, it would be significant if r was more NEGATIVE, which actually means less than. I hope this helps!
when we have a hypothesis testing and the equation they give tells us that x is a base so its not a power to anything and the x and y are equal to logs of something else, we still use the y=a+bx to find the pmcc of the coded data right?? in a level, will we have to use any other option than y=a+bx bc i domt remember doing questions where we didnt use that option
for the question at 21:02 why do we reject h0 when 0.5822 is less than 0.609 when the previous example did the opposite?
0.609 is the observed value, and it is bigger or 'more extreme' than the value of 0.5822 from the table - this is consistent with how we did this in the previous ones! :)
these are brilliant, any chance you know any of these kind of videos for physics :)
Ah good question, I’m not sure of any particular channels to recommend, but will ask my students who study physics and let you know!
z physics is very good
8:05 does this include being equal to 0.4428 too, or strictly greater than?
Hmmm I would say strictly greater than, although the value of r that you get from the calculator will likely be a very long number, so the change of it being exactly equal are very unlikely. I wouldn’t worry too much as they shouldn’t ask anything that’s a bit undecided like this! Stats doesn’t always have an exact answer I’m afraid!
@@BicenMaths Oh yeah, that's true 😂thanks
Hello sir, For 14:17 the r value < critical value so why was it not kinda accepted and for 10:26 the r value
It's not so much about which is greater than or which is less than, and rather whether the r value observed is more *extreme* than the critical value. But extreme, I mean if it is MORE negative than a negative critical value, or more positive than a positive critical value. If it is more extreme than the critical value, than the strength of observed correlation is high, meaning it is significant, and so we believe there to be correlation (i.e. we reject the null hypothesis).
hello seb, i am currently cramming for paper 3 thats happening next week. any tips? also, i cant find these product momeent coefficient tables in the formula booklet, where is it?
Page 37
Someone else has said where it is - towards the end of the booklet! Tips for Paper 3… I’d ask you to consider carefully which you do first, stats or mechanics, according to which you think will help you feel more comfortable quickly. Some like to do their weakest one first, others the stronger one so they have more time to look at questions they’re not sure about. Also take your time to read the Q carefully, and decide what the strategy is for the whole part of the question before starting. Good luck!
@@BicenMaths Thank you very much! I am definitely better at mechanics so I will probably start with that to get the maximum marks for it. Do you think I should spend the same amount of time for both sections?
If you think you need more time on stats, then I’d definitely jump over to it sooner than 1 hour. Might be best to do them all as quick as poss and then return at the end. Have a think what feels like it suits you best!
For the question at 21:06, why does the answer for part e) suggest using data from one place only?
Because the relationship between temperature and rainfall is likely to be different for different locations in the world - eg in the UK there’s usually more rain in cold weather/winter, but maybe in other locations they have hot wet summers! So just focusing on one location will help.
@@BicenMaths Oh I see, so would focusing on one location give them a more clear trend as opposed to the one shown in the diagram? And then this would give them a better idea of the relationship between rainfall and temperature?
@@nerimaken482 Yes that’s right, the data will show a clearer pattern as you’re just in one location. Correct!
@@BicenMaths Thank you so much! I know that was kind of a simple question but it still left me wondering about it for a while. I understand now.
Are there scenarios where you have to manually log the data in the table ? Also how would you determine which column to log if not both ?
I’ve never seen it in an exam, but it is in the textbook - you would literally just type log(value) for each value in your calculator and then you have the values to use for the graph
How do we know its two tailed at 12:20
Because the scientist believes that there is NO correlation - if she had said she believed there’s is negative correlation, it would be 1 tailed. Correlation just means p is not equal to 0
i figure that was it but wanted confirmation, thanks@@BicenMaths
Hi sir is there anything we need to know about the spearmans coefficient?
Nope, not part of the specification
so even for two tailed you can just show evidence using only one tail and thats enough for the marks? if you find no correlation from one tail you dont need to check the other tail for correlation because its symmetrical so the result is the same?
Yes only investigate the tail of the end that the observed value relates to. For example, if the observed correlation is negative, only check the negative end!
@@BicenMaths got it, thanks!
great video
Hi sir, in the previous page you said to reject h0 as r was greater than cv however in the first TTT Example you said to reject H0 even though r was smaller than the cv . I’m confused
Could u please explain 😅
It's about the magnitude of the observed r vs the critical value of r. If the magnitude of the observed value is greater than the magnitude of the critical value (i.e. ignoring negatives), reject H0.
Why is r being close to -1 suggesting an exponential model is appropriate? and also what is an explanatory variable?
If the data is coded to linear data, and then the value of r is close to -1, then the original data is likely exponential/non-linear. The explanatory variable is the one that explains the other one - for example, temperature change often causes other things to change, so is frequently an explanatory variable.
@@BicenMaths oh I was just illiterate the question actually had non-coded data and had r close to 1 so linear regression model was suitable. But i get what u mean when they code data by taking log y and stuff. Can we say the explanatory variable is the independent variable?
@@BicenMaths BTW thank u so much I went from giving up on this topic in class today to being able to do the exam questions at the end of the video
Yes that’s good! I was wondering where you got the bit about exponential from, I couldn’t find that question in the video 😆
So pleased you’re able to use my videos to supplement your lessons and feel confident! Keep up all the hard work, you’re clearly putting lots of time into maths, impressive stuff 👍🏼