00:12:16 Christopher Patterson: Hey! 00:12:21 Yulan Xie: hi! 00:12:23 Christopher Patterson: Just takin' it one day at a time xd 00:12:24 Maddy Griffith: Well! 00:12:28 Annalisa Watson (she/her): Feeling a little behind for this class! 00:12:35 Hiruni Jayasekera (she/her): agreed! 00:12:53 Julia Hankin: Same! I feel like we learned a lot of new big concepts really fast haha 00:12:54 Christopher Patterson: Will HW 5 solutions be posted soon? 00:12:57 Ijeoma Uche: Feeling lost in lecture lol 00:13:01 Nikki Marucut: Yes! @ Julia 00:13:21 Christopher Patterson: Copy, thanks. 00:13:22 Genesis Navarrete: nice to hear I’m not alone in feeling behind! 00:13:23 Phoenix Ding: cannot open the datahub 00:13:36 Nikki Marucut: Yes at @I Ijeoma 00:13:44 Rachel Harvill: @Phoenix I had the same issue in chrome, I had to open it using Safari 00:14:15 Mariah Jiles (she/her): my sisters coming into town from chicago! 00:14:15 Nikki Marucut: No! I have group projects 00:14:41 Julia Hankin: Mariah, yay sister time!! :) 00:14:57 Nikki Marucut: Chicago is beautiful! 00:14:58 Aliza Adler: @Hiruni plz share photos of the doggy!!! <3 00:15:11 Hiruni Jayasekera (she/her): hehe i will! 00:15:33 Mariah Jiles (she/her): Ikr Julia it’s gonna be fun! and it is @Nikki ☺️ 00:18:44 Karm Singh (she/her): p(A)*p(b) 00:21:18 Nadia Rojas: Can you go through #4 on the quiz? 00:24:04 Ekua-Yaaba Monkah: no? 00:26:18 Nadia Rojas: Yes, thank you! 00:29:35 Christopher Patterson: I multiplied and got it wrong on the quiz! The quiz solutions for me says to add 00:31:00 Hiruni Jayasekera (she/her): me too 00:31:05 Cristal Escamilla: same 00:31:07 Rachel Harvill: They aren’t independent 00:31:09 Hiruni Jayasekera (she/her): sol’n says to add then subtract 0,7 00:31:39 Christopher Patterson: ^ 00:31:49 Olufunke Fasawe: Me too. I multiplied and got the answer wrong in the quiz 00:32:00 Lillian Man (she/her): gradescope answer key says : the correct answer is P(HTN∩HLD) = P(HTN) + P(HLD) −P(HTN∪HLD) = 0.42 + 0.38 - 0.7 = 0.1 00:32:08 Yulan Xie: ^ 00:32:31 Rachel Harvill: We have to use the definition of the P(A or B) = P(A) + P(B) - P(A and B) 00:32:44 Hiruni Jayasekera (she/her): is that for dependent events? 00:33:29 Phoenix Ding: I think we can only multiply if the two events are independent, but here, it says they are comorbidities 00:34:17 Rachel Harvill: @Hiruni that is for independent and dependent events, for independent events P(A and B) = 0 00:34:30 Hiruni Jayasekera (she/her): @rachel gotcha, thank you! 00:34:49 Ariel Siegel: That’s how I calculated it ( .7 = .42 + .38 -x) 00:34:54 Stacy (Seohyun) Ahn: same 00:36:34 Lillian Man (she/her): yes 00:36:37 Hiruni Jayasekera (she/her): when can you multiply two events to find P(A and B)? 00:36:38 Yulan Xie: yes 00:38:25 Hiruni Jayasekera (she/her): yes 00:43:18 Ariel Siegel: I drew the tree to visualize this one 00:43:19 Olufunke Fasawe: For 6ii, when I plugged in the values into the formula, I got 0.1/0.25 = 0.4 00:45:07 Nadia Rojas: Could we theoretically find the probability P(L)? 00:47:56 Stacy (Seohyun) Ahn: lab please! 00:47:57 Christopher Patterson: Lets do lab ! 00:47:58 Ala Koreitem: Can we go over the lab 00:47:58 Ekua-Yaaba Monkah: lab 00:47:59 Aliza Adler: I’d like to get to the lab! 00:47:59 Chitra Nambiar: lab 00:47:59 Phoenix Ding: lab 00:48:00 Alexis O'Connor: I want to go over lab 00:48:03 Joyce Qiao: lab please 00:48:05 Mariah Jiles (she/her): I want to go over the lab 00:49:01 Christopher Patterson: mean and standard deviation ? 00:49:02 Hiruni Jayasekera (she/her): mean and sd? 00:49:06 Ijeoma Uche: Mean = 0 SD=1 00:49:35 Hiruni Jayasekera (she/her): always positive 00:50:26 Ala Koreitem: Density plots? 00:50:27 Nadia Rojas: histogram 00:50:31 Aliza Adler: Q-Q plots (can also use a histogram but it’s not as precise) 00:50:31 Rachel Harvill: The normal quantile plot? 00:50:31 Hiruni Jayasekera (she/her): histogram/bar chart? 00:50:34 Jessica Fields (she/her/hers): Histogram, bar graph, and QQ plot? 00:50:56 Hiruni Jayasekera (she/her): numerical 00:50:57 Ekua-Yaaba Monkah: numerical 00:51:01 Phoenix Ding: The Normal quantile plot, QQ plot? 00:52:06 Nadia Rojas: There are a fixed number of observations 00:52:07 Jessica Fields (she/her/hers): Discrete variable, happens n number of times, events are independent, and outcome is binary? 00:52:21 Ekua-Yaaba Monkah: n observations are independent 00:52:49 Nadia Rojas: The probability of success, p, is the same for each observation 00:54:06 Hiruni Jayasekera (she/her): independent occurrences 00:54:09 Jessica Fields (she/her/hers): There is no upper bound to the number of events? 00:54:09 Mariah Jiles (she/her): no upper bound? 00:58:06 Rachel Harvill: anorexia_diff <- anorexia %>% mutate(diff = (Postwt-Prewt)) 00:58:06 Julia Hankin: anorexia %>% mutate(diff= Postwt-Prewt) 00:58:06 Annalisa Watson (she/her): anorexia_diff <- anorexia %>% mutate(diff = (Postwt-Prewt)) 00:58:08 Ariel Siegel: anorexia_diff <- anorexia %>% mutate(diff = Postwt - Prewt) anorexia_diff dim(anorexia_diff) 00:58:50 Hiruni Jayasekera (she/her): continuous 00:59:05 Ekua-Yaaba Monkah: qqplot 00:59:08 Julisa Gaytan: histogram? 00:59:59 Annalisa Watson (she/her): p6 <- ggplot(data=anorexia_diff, aes(x=diff)) + geom_histogram(binwidth = 5) 01:01:11 Julisa Gaytan: unimodal 01:01:46 Julisa Gaytan: center and spread 01:01:46 Ijeoma Uche: Outliers 01:01:48 Ijeoma Uche: Range 01:01:55 Annalisa Watson (she/her): Median? 01:02:11 Stacy (Seohyun) Ahn: no 01:02:12 Ala Koreitem: Not really 01:02:24 Stacy (Seohyun) Ahn: center=0 01:02:33 Annalisa Watson (she/her): -10 to 20 01:03:03 Ijeoma Uche: Bimodal 01:03:17 Ijeoma Uche: 0 and 12isj 01:03:20 Ijeoma Uche: ish* 01:05:21 Phoenix Ding: p8 <- ggplot(anorexia_diff, aes(sample = diff))+ stat_qq()+ stat_qq_line()+ theme_minimal() p8 01:06:20 Nadia Rojas: Not normal 01:07:46 Leslie Giglio: Do we not have to put it into a data frame first? 01:07:46 Ekua-Yaaba Monkah: yes 01:07:46 Hiruni Jayasekera (she/her): could we go over it at the end if we have time? 01:07:52 Nikki Marucut: Yes ^ 01:08:04 Leslie Giglio: Ahh gotcha, thank you! 01:09:09 Rachel Harvill: pnorm 01:09:56 Nadia Rojas: pnorm(5, mean = 2, sd= 7, lower.tail = FALSE) 01:09:57 Leslie Giglio: 1-pnorm(q=5, mean=2, sd=7) 01:09:57 Maddy Griffith: 1 - pnorm(q = 5, mean = 2, sd = 7) 01:09:58 Hiruni Jayasekera (she/her): p9 <- pnorm(q = 5, mean = 2, sd = 7, lower.tail = FALSE) 01:10:43 Stacy (Seohyun) Ahn: above 90 percent of data 01:11:09 Olufunke Fasawe: qnorm? 01:11:24 Silvana Larrea: qnorm(0.90, 2, 7) 01:11:36 Nadia Rojas: no 01:12:19 Alexis O'Connor: yes :) feeling good about it 01:12:35 Anai Ramos: We can move on 01:13:56 Stacy (Seohyun) Ahn: X~Binom(n=20, p=0.27) 01:14:34 Annalisa Watson (she/her): events are independent, outcome is binary, probability of success is the same for each observation 01:17:24 Rachel Harvill: choose(n=20,k=5)*(.27^5)*(.73^15) 01:17:27 Leslie Giglio: choose(20,5)* (0.27)^5 * (0.73)^15 01:18:32 Annalisa Watson (she/her): dbinom(x=5, size =20, prob=.27) 01:19:34 Julia Hankin: Do you mind pausing for a moment 01:21:59 Olufunke Fasawe: So, where did the 15504 come from? 01:24:33 Julisa Gaytan: I think thta's the number of cases if we were to write out all possible combinations 01:24:35 Julia Hankin: Makes more sense now thank you! 01:24:39 Lupita Ambriz: Yes thank you for the break down! 01:26:32 Stacy (Seohyun) Ahn: 1-P(0) 01:26:32 Hiruni Jayasekera (she/her): 1? 01:27:39 Ijeoma Uche: 1-P(x=0) 01:27:55 Afroze Khan: 1 - P(x=1) 01:27:57 Julisa Gaytan: 1 - P(x=1) 01:31:25 Julisa Gaytan: i wasn't sure how to use the probabilities but the code I put in was 1 - pbinom(1, 20, .27) 01:32:27 Annalisa Watson (she/her): .73^20 01:32:54 Rachel Harvill: choose(n=20,k=0)*(.27^0)*(.73^20) 01:33:52 Annalisa Watson (she/her): (choose(20,1)*(.27^1)*(.73^19) 01:35:19 Hiruni Jayasekera (she/her): i’m still confused about why in pbinom we use 1 instead of 2 01:37:29 Hiruni Jayasekera (she/her): got it! 01:39:28 Annalisa Watson (she/her): 812*.27 01:40:28 Ekua-Yaaba Monkah: square root of mean 01:40:30 Ijeoma Uche: Sqrt 812*.27? 01:40:31 Annalisa Watson (she/her): sqrt(812*.27*(1-.27) 01:40:31 Rachel Harvill: sqrt(812*.27*(1-.27)) 01:43:05 Cristal Escamilla: I think you need c(mean, sd) 01:43:12 Rachel Harvill: You need to put mean and sd before assign p14 01:43:53 Nadia Rojas: N is large 01:43:54 Annalisa Watson (she/her): N needs to be large 01:44:27 Olufunke Fasawe: Pls what is the final answer for p14? 01:44:35 Olufunke Fasawe: OK. Thanks 01:44:47 Aliza Adler: Is it np >= 10 and n(1-p) >= 10 ? 01:46:02 Olufunke Fasawe: where does the >=10 come from? 01:48:19 Rachel Harvill: I’m confused, we can’t define y values in histograms 01:49:45 Hiruni Jayasekera (she/her): ^ 01:49:55 Stacy (Seohyun) Ahn: ^^ 01:50:18 Stacy (Seohyun) Ahn: stat_identity? 01:50:25 Annalisa Watson (she/her): Is it stat=“identity” 01:51:11 Annalisa Watson (she/her): I’m getting an error 01:51:12 Rachel Harvill: I get an error when adding stat=“identity” to geom_histogram 01:51:15 Rachel Harvill: jinx 01:51:18 Stacy (Seohyun) Ahn: ggplot2(obs_data, aes(x=x_vals)) + geom_histogram(stat="identity") 01:51:24 Stacy (Seohyun) Ahn: this gave me error too lol 01:51:30 Phoenix Ding: ggplot(obs_data, aes(x=x_vals, y=probs))+ geom_histogram(stat = "identity", binwidth = 50) 01:51:57 Annalisa Watson (she/her): What code is right? 01:52:22 Stacy (Seohyun) Ahn: Phoenix’s worked! 01:52:27 Hiruni Jayasekera (she/her): kelsey can we see your code? 01:52:29 Annalisa Watson (she/her): TY 01:53:31 Annalisa Watson (she/her): Ignoring unknown parameters: binwidth, bins, pad 01:53:50 Annalisa Watson (she/her): ok 01:54:25 Annalisa Watson (she/her): Can someone copy the ottr:: check for p16? I messed mine up 01:54:49 Stacy (Seohyun) Ahn: . = ottr::check("tests/p16.R") 01:54:58 Annalisa Watson (she/her): Thank you! 01:55:04 Stacy (Seohyun) Ahn: npnp 01:55:04 Olufunke Fasawe: . = ottr::check("tests/p16.R") 01:55:35 Hiruni Jayasekera (she/her): poisson distribuion because it’s rare? 01:56:00 Hiruni Jayasekera (she/her): there is no upper bound of events 01:56:21 Annalisa Watson (she/her): Probability is the same 01:56:45 Stacy (Seohyun) Ahn: X~Pois(5.7) 01:57:07 Hiruni Jayasekera (she/her): the average? 01:57:27 Phoenix Ding: sd 01:58:09 Annalisa Watson (she/her): Sqrt of lambda 01:58:50 Rachel Harvill: sqrt(5.7) 02:00:11 Ijeoma Uche: Im getting a failure for 18 02:00:28 Mariah Jiles (she/her): Same Ijeoma 02:00:29 Hiruni Jayasekera (she/her): e^mu*mu^k/k! 02:00:32 Lupita Ambriz: Can we go back up to 18 02:01:04 Hiruni Jayasekera (she/her): (forgot the negative mu) 02:01:41 Nadia Rojas: As k 02:01:42 Julisa Gaytan: e^-5.7 02:01:55 Julisa Gaytan: 5.7^0 02:02:03 Julisa Gaytan: 0! or 1 02:03:28 Rachel Harvill: dpois(x=0,lambda=5.7) 02:04:47 Stacy (Seohyun) Ahn: 1-P(x=0)-P(x=1) ? 02:04:50 Julisa Gaytan: cnaa we take the complement 02:06:07 Ala Koreitem: k 02:07:54 Annalisa Watson (she/her): 1- ppois(q=1, lambda=5.7) 02:10:37 Julisa Gaytan: 1 - ppois(12, 5.7) 02:10:56 Olufunke Fasawe: Can we see 20 02:11:01 Olufunke Fasawe: p20 again? 02:11:01 Anai Ramos: Can we see 18 02:11:05 Ijeoma Uche: Can we see 18 02:11:07 Nikki Marucut: Thanks Kelsey! 02:11:12 Ala Koreitem: Thank you! 02:11:14 Nikki Marucut: I hope you have a great weekend 02:11:20 Stacy (Seohyun) Ahn: Thanks so much Kelsey 02:11:44 Julia Hankin: Thank you Kelsey!! :) 02:11:46 Lupita Ambriz: Can we see 18 please