Level I CFA Quant: Hypothesis Testing-Lecture 1
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- Опубликовано: 27 июл 2024
- This is Reading 11 for the 2021 exam.
This CFA exam prep video lecture covers:
Hypothesis testing
- Stating the hypothesis
- Computing test statistic
- Determining critical value based on significance level
- Comparing test statistic with critical value
Two-tailed test
p-Value
Type I and Type II errors
Statistically significant versus economically meaningful
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Thnx sir .... for all such amazing vdos❤️
really good lecture. Available for free/ thanks to god and sir also.
Thanks for those videos! Really helpful and easy to understand!
You're very welcome!
IFT Support Team
how you calculate that critical value is 1.645?
Heartiest thanks for such videos. Love.
So nice of you
IFT Support Team
Why the z value for 5&% significance level is 1.65 not 1.96?
The 95th percentile point is 1.65: P(Z ≤ 1.65) = N(1.65) = 0.95 or 95 percent, and 5 percent of values remain in the right tail. Note the difference between the use of a percentile point when dealing with one tail rather than two tails. For the 90 percent confidence interval for two-tailed, 1.65 standard deviations is used where 5 percent of values lie outside that interval on each of the two sides. Here we use 1.65 because we are concerned with the 5 percent of values that lie only on one side, the right tail.
IFT support team
Still not clear on this sir
@@IFT-CFA even i did not undertand this
@@shantanujoshi6991 In one tail test Alpha of 10% would is 1.65. However, when it is two-tail test that becomes 10%/2 = 5%, so in this case we test both sides/tails, which is why we are testing at 1.65 which gives us 5% on both tail hence 10% of total alpha hence Z value is 1.65;
It will make sense when you are clear that if the test is one-tail or two-tail. E.g. if alpha was 10%; then one-tail test is 90th percentile for Z value is 1.65.
if alpha was 5%; then one tail test is 95th percentile for Z value is 1.96.
However, if the test is two tail then Alpha of 10% means 10/2=5% on both tails so you will use 95th percentile which is 1.96 - Note, if it was once tail test then you would have used 1.65.
@@IFT-CFA before the two-tailed slide, on the one-tailed test you used 1.65 for a 95% confidence level.
Thank you for this video, have spent days trying to understand this 😢
Thanks a lot for these lovely videos
Glad you like them!
IFT support team
Thank you sir! your videos are very helpful
Thank you for your kind words.
IFT Support Team
Thank you!
sir please repeat and summerise in one comment that when to use one tailed and double tailed test
its still confusing
Thank you sir so much
Thank you sir
How is 95% confidence level at 1.65?
the relation between CI and hypothesis test are shown here only about 2 tailed test? how to use one-tailed with CI?
the correspondence between a confidence interval and test of hypothesis relates to a two-sided test only.
IFT Support Team
can someone please explain where the critical value comes from? (at 7:53) thank you!
from Z Table
How do we calculate p-value from the test statistic?
To find the p-value by hand, we need to use the t-Distribution table with n-1 degrees of freedom. E.g, our sample size is n = 20, so n-1 = 19.
In the t-Distribution table, we need to look at the row that corresponds to “19” on the left-hand side and attempt to look for the absolute value of our test statistic 1.49. Notice that 1.49 does not show up in the table, but it does fall between the two values 1.328 and 1.729.
Next, we can look at the two alpha levels at the top of the table that correspond to these two numbers. We see that they are 0.1 and 0.5. This means that the p-value for a one-sided test is between 0.1 and 0.05. Let’s call it .075. Since our t-test is two-sided, we need to multiply this value by 2. So, our estimated p-value is .075 * 2 = 0.15.
IFT Support Team
Great video
Thanks!
Significance level = Probability of a type I error.. But how to calculate probability of a type II error? You said 1-P, but where do we get the P from? Is it given or do we calculate it?
The probability of a Type I error in testing a hypothesis is denoted by the Greek letter alpha, α. This probability is also known as the level of significance of the test. For example, a level of significance of 0.05 for a test means that there is a 5 percent probability of rejecting a true null hypothesis. When we conduct a hypothesis test, we generally specify level of significance, i.e. P.
IFT Support Team
Hi Alex, perhaps it's easier if you think in terms of Confidence Interval, rather than in terms of alpha. If we say that alpha is 5%, this means the level of significance is 5%. 1 - alpha is equal to the % value of confidence interval. Therefore, you are 95% confident that the results you will calculate will generate a reliable outcome. What does this mean? That you are not 100% sure, only 95%. 100% - 95% is 5% (which is equal to the level of significance), and is the probability of accepting a null hypothesis which is in reality not true.
@@marcomolinari7971 5% chance will accept null hypothesis
Atleast watched 5 times to understand critically
24:27 i thought this was the 0.05 was the significance level, but you're saying it's the p-value...
Anyways, thanks for these videos.
It is the p-value.
IFT Support Team
king
at 95%, the critical value is 1.96. Throughout the whole video its been taken as 1.65, why?
For a one-tailed test with a significance level of 5%, the critical value will be 1.65. This is because on the z-table, a significance level of 0.05 corresponds to a critical value of 1.65. Please watch from 6:43 to see the one-tailed test visually represented.
For a two-tailed test with a significance level of 5%, the critical value will be +/- 1.96 as the 5% is divided between the two tails, each tail having 2.5%. Please see the graph at 15:25 for a visual representation.