1 00:00:00,000 --> 00:00:04,350 Hello and welcome to this course on statistics. 2 00:00:04,350 --> 00:00:07,200 In this course, our goal is to 3 00:00:07,200 --> 00:00:09,975 make learning statistics fun and 4 00:00:09,975 --> 00:00:12,615 enable you to apply statistical methods 5 00:00:12,615 --> 00:00:16,020 for data analysis and Data Science. 6 00:00:16,020 --> 00:00:18,270 My name is Murtaza Haider, 7 00:00:18,270 --> 00:00:20,430 I'm your instructor for this course. 8 00:00:20,430 --> 00:00:22,950 I'm also an associate professor at 9 00:00:22,950 --> 00:00:24,480 the Ted Rogers School of Management at 10 00:00:24,480 --> 00:00:27,325 Ryerson University in Toronto. 11 00:00:27,325 --> 00:00:31,460 The author of Getting Started with Data Science, 12 00:00:31,460 --> 00:00:34,025 Making Sense of Data with Analytics. 13 00:00:34,025 --> 00:00:36,949 My research interests are in urban economics 14 00:00:36,949 --> 00:00:40,505 as they relate to housing markets and transportation. 15 00:00:40,505 --> 00:00:42,830 I blog regularly, and you can 16 00:00:42,830 --> 00:00:45,275 find my blogs on Huffington Post. 17 00:00:45,275 --> 00:00:46,970 By way of training, 18 00:00:46,970 --> 00:00:49,250 I have a Master's in Transportation Engineering 19 00:00:49,250 --> 00:00:50,390 and Planning and 20 00:00:50,390 --> 00:00:52,310 a PhD in Civil Engineering 21 00:00:52,310 --> 00:00:55,560 with a focus on Urban Systems Analysis. 22 00:00:55,630 --> 00:00:59,240 My name is Aije Egwaikhide. 23 00:00:59,240 --> 00:01:02,780 I'm the co-instructor for this course. 24 00:01:02,780 --> 00:01:06,245 I'm a Senior Data Scientist and Statisticians 25 00:01:06,245 --> 00:01:10,280 with the IBM developers skills networks team. 26 00:01:10,280 --> 00:01:14,285 I have field experience working on supervised and 27 00:01:14,285 --> 00:01:16,850 unsupervised Machine Learning algorithms 28 00:01:16,850 --> 00:01:19,085 for oil and gas clients. 29 00:01:19,085 --> 00:01:21,635 During my high school in Nigeria, 30 00:01:21,635 --> 00:01:24,650 it was easy to put off mathematics and 31 00:01:24,650 --> 00:01:28,550 statistics and focus on the seemingly easier courses. 32 00:01:28,550 --> 00:01:31,145 I always love a good challenge. 33 00:01:31,145 --> 00:01:34,160 My interest in statistics and mathematics 34 00:01:34,160 --> 00:01:35,660 spiked as a result of 35 00:01:35,660 --> 00:01:38,180 people around me saying it was hard. 36 00:01:38,180 --> 00:01:42,020 So I made my parents invest in textbooks 37 00:01:42,020 --> 00:01:46,115 and I always made sure to be ahead of the class. 38 00:01:46,115 --> 00:01:49,235 When I got to the University of Manitoba 39 00:01:49,235 --> 00:01:50,840 for my undergrad, 40 00:01:50,840 --> 00:01:55,835 picking statistics alongside economics was easy. 41 00:01:55,835 --> 00:01:58,520 When I had to do a postgrad, 42 00:01:58,520 --> 00:02:01,475 picking Data Science and Business Analytics 43 00:02:01,475 --> 00:02:03,020 was a no-brainer. 44 00:02:03,020 --> 00:02:04,875 On my off days, 45 00:02:04,875 --> 00:02:10,235 I'm a fashion and carrier blogger on Instagram. 46 00:02:10,235 --> 00:02:13,310 This course consists of 47 00:02:13,310 --> 00:02:18,890 five modules: Introduction and Descriptive Statistics, 48 00:02:18,890 --> 00:02:21,635 Data Visualization, 49 00:02:21,635 --> 00:02:25,055 Introduction to Probability Distribution, 50 00:02:25,055 --> 00:02:30,290 Hypothesis Testing, and Regression Analysis. 51 00:02:30,290 --> 00:02:35,045 Each module will comprise of four to six videos, 52 00:02:35,045 --> 00:02:40,505 and we'll include exercises for you to practice on. 53 00:02:40,505 --> 00:02:43,175 The hands-on lab will utilize 54 00:02:43,175 --> 00:02:47,570 Jupiter Notebooks using the Python programming language, 55 00:02:47,570 --> 00:02:49,490 which is one of the easiest 56 00:02:49,490 --> 00:02:51,875 programming languages to learn. 57 00:02:51,875 --> 00:02:56,490 Let's get started and happy learning.