00:09:55 Alexis O'Connor: good :) 00:09:56 Christopher Patterson: Whats up!!!!!!!!! 00:09:58 Ekua-Yaaba Monkah: Hello! Doing good! 00:10:00 Julia Hankin: Holding in there!! 00:10:06 Jessica Fields (she/her/hers): Feeling busy! Not the biggest fan of exam on a Friday... 00:10:06 Gabriela Gonzalez: stressed :’( 00:10:42 Samantha Krutzfeldt: im terrified for this exam 00:10:47 Gabriela Gonzalez: ^^ 00:11:12 Mariah Jiles (she/her): ^^^ 00:11:17 Ijeoma Uche: Are the practice midterms a good predictor for the exam? 00:11:26 Ekua-Yaaba Monkah: normal distribution 00:11:37 Anai Ramos: Poisson 00:11:39 Hallie Roth (she/her): Probability (disjoint, joint, independent events, etc) 00:11:42 Maddy Cuyler: Hypothesis testing 00:11:42 Samantha Krutzfeldt: probability problems 00:11:48 Ijeoma Uche: Probability, key differences about passion and binomial 00:11:49 Maddy Griffith: Hypothesis testing 00:11:56 Lauren Faciana: Probability problems 00:12:04 Ijeoma Uche: Midterm questions!! 00:12:04 Michele Ko (she/her): +1 hypothesis testing 00:12:08 Nadia Rojas: Continuity correction for normal approximation to binomial distributions 00:12:10 Leslie Giglio: Probability 🙏 00:12:12 Genesis Navarrete: probability problems, conditional and tree diagrams 00:12:17 Samantha Krutzfeldt: midterm questions 00:12:30 Taylor Zehren: +1 continuity correction 00:12:31 Gabriela Gonzalez: Probability 00:12:34 Yulan Xie: ^ 00:13:48 Ijeoma Uche: Do we need to calculate P(A and B) or is it given? 00:13:54 Ijeoma Uche: I get confused about that 00:14:37 Annalisa Watson (she/her): I think it would depend on the question? 00:14:55 Hallie Roth (she/her): Is the “and” synonymous with intersection in these statements? 00:14:57 Gabriela Gonzalez: same @Ijeoma 00:16:37 Ekua-Yaaba Monkah: can you please repeat what you said about independence/dependence? 00:18:40 Annalisa Watson (she/her): Does the union also mean both? 00:18:41 Olufunke Fasawe: and what if they are dependent? 00:19:07 Ala Koreitem: Do you only use bayes’ theorem if A and B are independent? 00:19:09 Samantha Krutzfeldt: in the notes it confuses me when it says disjoint events are always dependent but then also says they can never happen together?? that makes me think independent? 00:19:47 Hallie Roth (she/her): So, in the case that A and B are independent, is there ever an intersection? Since, we calculate P(A) * P(B), rather than P(A intersect B) 00:19:58 Ijeoma Uche: Can you go over the first example on how to check it 00:22:31 Ijeoma Uche: What is P(A and B) when it is dependent? 00:22:35 Shannon Mohler: I apologize if you've already gone over this but can you go over the difference between independent/dependent and disjoint/joint? 00:22:50 Hallie Roth (she/her): +1 shannon 00:26:20 Gabriela Gonzalez: maybe we can do a question from one of the practice exams? i think it would be helpful to see this applied to an actual problem 00:27:45 Lauren Faciana: ^ Fall 2020 midterm number 13 is a good probability example 00:29:23 Annalisa Watson (she/her): All possible outcomes 00:29:24 Maddy Cuyler: All possible events 00:29:37 Aliza Adler: I’m trying to do the fall 2020 midterm exam timed later so don’t want to hear the answers ahead of time- any chance someone can send a message in the chat when we’re done reviewing this problem? 00:29:40 Ala Koreitem: 1 00:29:49 Annalisa Watson (she/her): Aliza I can! 00:29:55 Aliza Adler: Ty! :) 00:31:47 Ijeoma Uche: Do we have to include the range of the sample space? 00:32:11 Hallie Roth (she/her): Add them 00:32:21 Gabriela Gonzalez: Add P(A) + P(B) 00:32:31 Gabriela Gonzalez: so P(BC) + P(UC) 00:33:58 Ijeoma Uche: {0,1} 00:34:05 Ijeoma Uche: [0,1] 00:34:21 Ekua-Yaaba Monkah: so would having BC and UC be dependent or independent? 00:34:29 Julia Hankin: If we weren’t assuming that a woman will only be diagnosed with 1 type of cancer, could we figure out the intersection? 00:34:47 Lupita Ambriz: indep 00:34:48 Lauren Faciana: dependent 00:34:49 Ijeoma Uche: Dependent 00:34:54 Gabriela Gonzalez: independent 00:34:56 Ijeoma Uche: disjoint 00:34:58 Ala Koreitem: dependent 00:34:59 Annalisa Watson (she/her): Dependent bc they are mutually exclusive 00:37:05 Ijeoma Uche: Binomial? 00:37:32 Ijeoma Uche: What would it look like if it was poisson 00:38:26 Maddy Cuyler: @Ijeoma I think we wouldn’t have a defined sample size if it was poisson 00:38:46 Leslie Giglio: 1-P(x=0) 00:38:48 Michele Ko (she/her): Take the complement 00:38:49 Annalisa Watson (she/her): 1-P(0) 00:40:33 Gabriela Gonzalez: where is 10 coming from? 00:40:44 Ala Koreitem: ^ 00:40:50 Maddy Cuyler: Sample size 00:40:55 Julie Grassian (she/her): Can you explain why p(0) is .259 to the 10th power? 00:40:56 Annalisa Watson (she/her): The question says 10 women have cancer know their diagnoses 00:41:16 Gabriela Gonzalez: I missed that ^^ thank you both! 00:41:45 Kelsey Conklin: So would it be the complement of 0.259, or 0.741? 00:42:15 Hallie Roth (she/her): yeah i figured (1-.259)^10 00:42:38 Michele Ko (she/her): ^ 00:44:23 Hallie Roth (she/her): These are the kinds of questions that make me wonder why our time limit is 75 minutes lol 00:44:31 Maddy Cuyler: ^^^ 00:44:32 Annalisa Watson (she/her): ^^ 00:44:33 Leslie Giglio: Isn’t it also [1- (10 choose 0)(0.259)^0(0.741)^10] ? (In the full form) 00:45:42 Gabriela Gonzalez: is that formula the binomial coefficient? or am I getting confused with something else? 00:45:42 Hiruni Jayasekera (she/her): should it be 1-.259 in the parentheses? 00:46:05 Annalisa Watson (she/her): That’s right Gaby 00:46:24 Hiruni Jayasekera (she/her): Calculates the probability of observing x successes when x is distributed binomially (that’s what i have in my notes) 00:46:47 Ekua-Yaaba Monkah: whats the formula for the binom distribution again? 00:47:18 Hiruni Jayasekera (she/her): n choose k * p^k * (1-p)^n-k 00:47:40 Ekua-Yaaba Monkah: bless 00:51:54 Ekua-Yaaba Monkah: yes 00:52:12 Annalisa Watson (she/her): @Aliza we’re not working on the question anymore 00:52:28 Aliza Adler: ty! 00:53:51 Gabriela Gonzalez: does someone mind typing what we plugged in when we used the binomial distribution for P(at least 1 of them has BC) ? I didn’t get a chance to write it down 00:53:58 Shannon Mohler: binomial distribution 00:53:59 Cristal Escamilla: binomial? 00:54:35 Michele Ko (she/her): P(X=0) + P(x=1)? 00:55:30 Nadia Rojas: How do you do six choose 0 by hand? 00:55:53 Nadia Rojas: Thank you! 00:55:57 Hiruni Jayasekera (she/her): pbinom where q = 1? 00:57:24 Samantha Krutzfeldt: there was an example in midterm 2019 I think Q5 g. where it was binomial but they used pnorm??? 00:58:05 Ijeoma Uche: Binomial , pbinom(3) 00:58:15 Hiruni Jayasekera (she/her): pbinom(2,6,.3,lower.tail=false) 00:58:27 Ijeoma Uche: 1-pbinom(3) 00:58:49 Hallie Roth (she/her): so with lower.tail = false, it will not include 2? 01:01:03 Michele Ko (she/her): If it were x > 3, would it be 1- [P(0) + P(1) + P(2) + P(3)]? And pbinom(3, size=, prob=, lower.tail =F) 01:01:15 Annalisa Watson (she/her): So is pbinom used to calculate the probability at and below a given number 01:01:18 Annalisa Watson (she/her): ? 01:01:52 Ijeoma Uche: 1- pbinom(3,6,.3) 01:02:12 Michele Ko (she/her): Thank you!! <3 01:06:29 Gabriela Gonzalez: there’s also tables in the review slides with the functions for each distribution and when to use them :) just in case anyone hasn’t seen those 01:10:31 Ijeoma Uche: Why would we need to add the lower.tail=F if we are only look for a specific value 01:11:37 Ijeoma Uche: For qnorm 01:12:15 Justin Nguyen: would we ever use z score for pbinom/ppois? 01:13:11 Justin Nguyen: couldn't we approximate pnorm for pbinom? 01:13:21 Justin Nguyen: oh nvm thank you 01:13:38 Samantha Krutzfeldt: so for dbinom and dpois we would never use lower.tail = F 01:13:50 Ijeoma Uche: Would you mind telling us which ones to use for binomial and poisson 01:14:07 Ijeoma Uche: Codes 01:14:23 Hallie Roth (she/her): hypothesis testing 01:14:26 Hiruni Jayasekera (she/her): continuity correction 01:14:33 Hiruni Jayasekera (she/her): +1 hypothesis testing too! 01:14:36 Annalisa Watson (she/her): +1 for both of those! 01:15:16 Annalisa Watson (she/her): There is one but I don’t remember where 01:16:22 Annalisa Watson (she/her): It’s 5g on fall 2018 for continuity correction 01:16:24 Michele Ko (she/her): For hypothesis testing, question 10 in the 2020 midterm is an example 01:16:48 Samantha Krutzfeldt: did you say why we use pnorm for binomial 01:18:30 Hiruni Jayasekera (she/her): pbinom(6999,10000,.67,lower.tail=false)? 01:18:32 Hallie Roth (she/her): 1 - pbinom(6700, n, prob) 01:19:01 Julie Grassian (she/her): pbinom(6700, size = 10,000, prob = .67, lower.tail = F) 01:21:51 Gabriela Gonzalez: 0.33 is the SD right? 01:22:50 Annalisa Watson (she/her): .33 is the complement of the probability (.67) - is that what you’re asking? 01:22:52 Leslie Giglio: 0.33 is the probability of not having senioritis (1-0.67)^ 01:23:06 Gabriela Gonzalez: oh my bad haha - yes thank you @annalisa @leslie 01:26:56 Nadia Rojas: How do you know when you add versus subtract 0.5? 01:27:01 Michele Ko (she/her): ^ 01:27:41 Annalisa Watson (she/her): Yes 01:27:46 Kelsey Conklin: We choose to add or subtract depending on which way will get us more of the area under the curve 01:28:13 Gabriela Gonzalez: i’m still really confused with this question. i don’t remember when we talked about these formulas and how to apply them 01:28:23 Ekua-Yaaba Monkah: ^ 01:28:25 Hiruni Jayasekera (she/her): it’s in the lecture on binomial 01:28:32 Michele Ko (she/her): Yes in lecture we did — 1250 count is the interval between 1249.5 and 1250.5. Thus, we should compute P(X >= 1249.5) rather than P(X > 1250) for an even more accurate answer. Here is the more precise estimate for the example: 1- pnorm(q = 1249.5, mean = 1240 , sd = 21.70714) 01:28:33 Hiruni Jayasekera (she/her): pg 13 01:29:00 Gabriela Gonzalez: @Hiruni is this stuff about N(mean = np, sd = ) and all that in there? 01:29:05 Annalisa Watson (she/her): This is what I have in my notes for the continuity correction but I’m not sure if it’s right 01:29:11 Annalisa Watson (she/her): Add .5 when we are looking at less than the #, subtract .5 when we are looking at greater than or equal to (and use the complement) 01:29:19 Annalisa Watson (she/her): Sorry if it’s incorrect or confusing 01:29:22 Hallie Roth (she/her): ^ same Annalisa 01:29:24 Michele Ko (she/her): Ohhhh @kelsey @annalisa thank you!! 01:29:28 Nadia Rojas: Thank you ^ 01:29:51 Hiruni Jayasekera (she/her): @gabriela yeah! right below that there’s an example for cont correction 01:30:28 Gabriela Gonzalez: @Hiruni thanks so much! i’ll have to go back and take a look 01:30:47 Leslie Giglio: That’s super helpful Annalisa, thank you!^ 01:31:02 Hiruni Jayasekera (she/her): thank you annalisa that is helpful!! 01:32:44 Gabriela Gonzalez: why 0.5 though? 01:32:59 Gabriela Gonzalez: and what is the purpose of the continuity correction? i don’t get what it’s doing and why we use it 01:33:27 Gabriela Gonzalez: sorry i have so much questions lol :’( 01:33:43 Ijeoma Uche: Would we have something like this on the midterm? 01:36:05 Gabriela Gonzalez: i’m ready to move on 01:36:22 Hallie Roth (she/her): evidence for/against the null 01:36:33 Michele Ko (she/her): question 10 in the 2020 midterm is an example of hypothesis testing if folks want to do a problem 01:36:40 Ijeoma Uche: Could we do screening too ? 2020 question 9 iii, iv 01:37:14 Samantha Krutzfeldt: so the only reason we use pnorm in that last one is because they are asking for the continuity correction???? since its binomial 01:38:04 Samantha Krutzfeldt: anyone? lol 01:38:32 Lauren Faciana: 2300 01:39:00 Lauren Faciana: Because the 3225 is the mean of our sample 01:39:05 Ala Koreitem: 3225 is x bar 01:39:18 Samantha Krutzfeldt: im still confused on the last one if anyone can clarify my question above would be awesome 01:39:21 Hiruni Jayasekera (she/her): @sam i’m not totally sure but i think it’s because we’re doing the correction because the binomial distribution is approaching the normal distribution 01:39:39 Michele Ko (she/her): @Samantha, I think the same as @hiruni 01:39:40 Samantha Krutzfeldt: thank you @hiruni 01:39:54 Samantha Krutzfeldt: thank you @michele 01:39:54 Ijeoma Uche: Not equal 01:39:55 Annalisa Watson (she/her): Yeah that’s right Samantha, and because in the previous problem f they kind of set the scene to the concept that we can use the normal approximation for the binomial distribution 01:40:09 Samantha Krutzfeldt: thank you 01:40:11 Hallie Roth (she/her): mu > 2300 01:41:02 Hallie Roth (she/her): So the fact that the CDC recommendation is “no more than” 2300 mg, is not relevant for the test? 01:41:02 Maddy Cuyler: Samantha Normal approximation for binomial distributions are on page 13 of the binomial lecture! It has the rules there and an example 01:41:07 Ekua-Yaaba Monkah: SE 01:41:08 Justin Nguyen: SE 01:41:08 Gabriela Gonzalez: standard error 01:41:31 Shannon Mohler: x bar is our sample mean 01:41:47 Lauren Faciana: 3225 01:41:48 Maddy Cuyler: 3225 01:41:48 Shannon Mohler: 3225 01:42:19 Lauren Faciana: 200/ sqrt 100 01:43:28 Ijeoma Uche: 95% = 1.96 01:43:39 Shannon Mohler: z star is a set value based on the CI for 95% I think its around 2 01:45:01 Lillian Man (she/her): qnorm? 01:45:19 Maddy Cuyler: We were told in lecture that we could use 2 but some of the practice midterms were calculated with 1.96. Can we use either or should we go with 1.96? 01:45:26 Maddy Cuyler: For the 95% CI 01:45:46 Annalisa Watson (she/her): I think I saw in the answer key that you can use either 01:46:53 Lillian Man (she/her): qnorm(0.95, mean = 0, sd =1) 01:49:02 Shannon Mohler: 2.5% 01:49:02 Hiruni Jayasekera (she/her): 0.025 01:50:06 Samantha Krutzfeldt: qnorm(0.025, 0,1,lower.tail = F) 01:52:57 Samantha Krutzfeldt: what is the notation you are writing under your z* 01:53:05 Samantha Krutzfeldt: 1-a/2? 01:54:04 Gabriela Gonzalez: I remember the equation from class not including the 1-a/2 01:54:27 Gabriela Gonzalez: it was just x-bar plus/minus z * SD/sqrt(n) 01:54:48 Annalisa Watson (she/her): I don’t think we need to know 1-a/2 for the test 01:55:19 Gabriela Gonzalez: the 1-a/2 was included in the review slides so i got confused 01:55:41 Ijeoma Uche: Could we do screening too ? 2020 question 9 iii, iv 01:55:58 Ekua-Yaaba Monkah: so we don't need to memorize the equation for Z*? 01:56:42 Justin Nguyen: so do we only need to know 90,95, and 99% CIs for the midterm? 01:57:18 Samantha Krutzfeldt: she said we need to know how to do it so i'm assuming we may need to calculate it for another value ? 01:58:16 Gabriela Gonzalez: was the CI for the problem we were doing (3185.8, 3264.2) ? 01:58:44 Annalisa Watson (she/her): Can you finish with the interpretation for the question 01:58:51 Hiruni Jayasekera (she/her): +1^ 01:59:25 Annalisa Watson (she/her): That’s right Gaby 01:59:56 Gabriela Gonzalez: 🤠🎊 02:01:03 Lauren Faciana: no 02:02:16 Annalisa Watson (she/her): less 02:02:16 Maddy Cuyler: Less? 02:02:30 Lauren Faciana: because we have to reject the null 02:04:03 Annalisa Watson (she/her): So the confidence interval refers to the sample? 02:05:04 Annalisa Watson (she/her): Or it refers to the population distribution but using to x bar 02:13:02 Hallie Roth (she/her): Less