Statistics for Data Science (Crash Course) (Day-13) |

[@Codanics]

Watch the complete video with patience and in HD.....

[@goharrahman5611]

12:30 Average Maximum Max Minimum Prediction Varience

[@muhammadzohaib8517]

BEST Part IS Jiny Lor ni Dikheya o Jamya e Ni

[@SaeedAhmad-ny9nl]

Baba je Faisalabad

[@ayeshaabdullah3579]

your videos are no complete. there is no videos for day 12 and after 11b. please if this is free share videos

[@sohaibahmad4627]

​@@goharrahman5611l

[@SHKIIUI]

48:40 - 49:00 sum_Iris = Iris["sepal_length"].sum() mean_Iris = Iris["sepal_length"].mean() median_Iris = Iris["sepal_length"].median() mode_Iris = Iris["sepal_length"].mode()

[@mh5_4_01]

15:06 / 1:06:08 • Statistics terms 1. Average 16. t-test 2. Population 17. ANOVA 3. Random sample 18. MANOVA 4. Estimator 5. Bias 6. Sample mean 7. Sample variance 8. Chi-Squared relation with sample variance 9. Confidence Intervals 10. Maximum 11. Minimum 12. Height 13. Percentage 14. Likelihood 15. Variance

[@tayyabashahid6872]

12:27 Average income Highest score in cricket Fastest/ maximum speed Least number of runs Percentage of teachers Raining prediction Variability Comparison Classification

[@adenrajput8531]

8:06 Data Analyst: 1. Collaborating with organizational leaders to identify informational needs 2. Acquiring data from primary and secondary sources 3. Cleaning and reorganizing data for analysis 4. Analyzing data sets to spot trends and patterns that can be translated into actionable insights 5. Presenting findings in an easy-to-understand way to inform data-driven decisions Data Scientist: 1.Gathering, cleaning, and processing raw data 2. Designing predictive models and machine learning algorithms to mine big data sets 3. Developing tools and processes to monitor and analyze data accuracy 4. Building data visualization tools, dashboards, and reports 5. Writing programs to automate data collection and processing

[@wasifmughal4519]

@ 1:05:49 Bht conceptual based thi or bht easy kr k smjhaya gya hai easily smjh agae statistics ki basics tarky wali examples k sth

[@rabiaattiq6953]

02:06 Like and going to watch whole video 08:17 Data analyst: deals with the analysis of known data using SQL, python and R language. They perform day to day activity and extract pattern and identify trends from data. Data scientist: develop models to deal with the unknown data, bigger scope than data analyst. Make framework and algorithm to collect data. Deals with machine learning algorithm 15:02 Mean (average), median, mode, maximum, minimum, probability (likelihood), variance, t-test, anova, correlation factor, standard deviation, standard error, f-test, Percentage (Ratio), Z-test, Chi-square 18:04 irrigation is missing 25:10 Another example of interval variable data is measurement of pH value of water. pH = 0 doesn't mean no acidity 28:38 Covid data was based on Population 59:50 All clear and thank you codanics 01:06:00 Yes video is well illustrated and well explained with lots of engaging examples 👍

[@Ijazalijin]

all-clear thanks codanics for teaching us statistics for data science in this python ka chilla

[@furqan041]

thank you codanics for teaching us datascience with python

[@tayyabarani9176]

All Clear...Thankyou Codanics for teaching us data science with Python

[@Asad.UrRahman]

25:03 Interval Variable examples 1- Voltage e.g. 110 and 120 volts (AC); 220 and 240 volts (AC) and etc. 2- Grade levels in a school (1st grader, 2nd grader, and etc.) 3- Dates (1015, 1442, 1726, etc.) Etc

[@AussieTravels_Vic]

15:02 Mean (average), median, mode, maximum, minimum, probability (likelihood), variance, t-test, ANOVA, correlation factor, standard deviation, standard error, f-test, Percentage (Ratio), Z-test, Chi-square

[@AbdulHannan-dg6dl]

8:18 Simply put, a data analyst makes sense out of existing data, whereas a data scientist works on new ways of capturing and analyzing data to be used by the analysts. 9:45 #yaar(audio) 10:57 Average Max Max Min Percentage Likelihood Varience T-test Annova 11:58 Baba G Faisalabad 15:09 Descriptive statistics inferential statistics Sample vs population Quantitative and Qualitative variables 18:02 Please irrigation wala wahan pr likh dein 21:56(audio) 25:56 In interval true zero is meaningful like 0 centigrade is cooler temperature. order, categories, natural order, and intervals. 28:29 Sample 29:24 Cheatsheet 48:07 df.to_csv 48:53 import numpy speed = [99,86,87,88,111,86,103,87,94,78,77,85,86] x = numpy.mean(speed) print(x) import numpy speed = [99,86,87,88,111,86,103,87,94,78,77,85,86] x = numpy.medain(speed) print(x) 59:51 All clear thank you codanics for teaching us statistics 1:03:10 Han G Hum Lahore Gye Thy 1:06:04 Baba g Faislabad

[@muhammadahmadihsan2212]

Like kar dya, comment kr dya aur video puri deikh li. Very informative

[@R-R957]

like kr diya ha aur complete watch krun ga baba g

[@sahiljatoi813]

36:55 Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (mostly graphical) to maximize insight into a data set; uncover underlying structure; extract important variables; detect outliers and anomalies; test underlying assumptions; develop parsimonious models; and determine optimal factor settings.

[@Ijazalijin]

👍👍 jab tak pora daikengai nahi tb tak chorain gai nahi.

[@AnasShehzadofficial1]

Learning completely Video Inshallah Dr sahib the Great Person

[@ahmadansari7708]

Timestamp 59:55 All clear Thank you codanics for teaching us all concepts of basic data science.

[@InfobyAR]

36:50 Exploratory data analysis (EDA) is the first step in the data analysis process. Researchers and data analysts use EDA to understand and summarize the contents of a dataset, typically with a specific question in mind, or to prepare for more advanced statistical modeling in future stages of data analysis.

[@iqramahmood9667]

8:18 Data analyst is one who collects the data, cleans and analyzes it and interprets the results of the analysis. A data scientist is someone who can predict the future based on past patterns whereas a data analyst is someone who merely curates meaningful insights from data. A data analyst addresses business problems but a data scientist not just address business problems but picks up those problems that will have the most business value once solved

[@muhammadowaiskhan4132]

37:00 Exploratory Data Analysis refers to the critical process of performing initial investigations on data so as to discover patterns,to spot anomalies,to test hypothesis and to check assumptions with the help of summary statistics and graphical representations.

[@aminaabdulrehman1923]

The major difference between data science and data analytics is scope. A data scientist’s role is far broader than that of a data analyst, even though the two work with the same data sets. A data scientist often uses machine learning, database management, and data wrangling to create and organize data sets, while a data analyst uses SQL, R or Python programming languages, data visualization software, and statistical analysis to collect and interpret data. A data analyst tends to focus on a specific area (e.g. sales, e-commerce) while a data scientist takes a holistic view of how an organization runs.

[@sehrishilyas8416]

8:00 Data engineer - process the obtained data so that it is ready for analysis, Data analyst - prepare advanced analyses and Data scientist - employs traditional statistical methods or unconventional machine learning techniques for making predictions.

[@talhanisarmughal]

25:25 Example of interval variable/data: Suppose three persons work in a company and earn in dollars. 1st person salary is 5000$, 2nd person salary is 10,000$ and 3rd person salary is 15,000$. You can see it as an interval because the difference is meaningful which is 5000$.

[@SyedaAbbas-x7d]

Dr. Aammar, you are an awesome instructor. I watched the whole video, made Notes, and saved in my Notebook for practice. I don't have any coding background, but I am so happy to have an Instructor like you, who is teaching us honestly from scratch, I really appreciate all your efforts, time, and support.

[@sahiljatoi813]

59:48 All clear Thank you condanics for teaching all concepts statistics for data science with python

[@zohaibRahman-l5k]

Ap ki waja se sir maine Data Science field main aya ... Alot Of Thanks

[@waqasahmad8170]

@37:00 Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods. It helps determine how best to manipulate data sources to get the answers you need, making it easier for data scientists to discover patterns, spot anomalies, test a hypothesis, or check assumptions.

[@muhammadrizwan688]

@8:18 - Data analysts: typically work with structured data to solve tangible business problems using tools like SQL, R or Python programming languages, data visualization software, and statistical analysis. - Data scientists: often deal with the unknown by using more advanced data techniques to make predictions about the future. They might automate their own machine learning algorithms or design predictive modeling processes that can handle both structured and unstructured data. This role is generally considered a more advanced version of a data analyst.

[@musharafahsan9846]

59:47 All clear Thank you codanics for teaching us statistics for data science......

[@ahmadansari7708]

Timestamp 15:01 Terms of statistics Average, Maximum, Minimum, Mode, Median, Mean, Percentage, Likelihood, t-test, varience.

[@zainshahid798]

08:16 The best answers I found on-net regarding the difference between data scientist and data analyst is as: “A data scientist is someone who can predict the future based on past patterns whereas a data analyst is someone who merely curates meaningful insights from data.” “A data scientist job roles involves estimating the unknown whilst a data analyst job roles involves looking at the known from new perspectives.” “A data scientist is expected to generate their own questions while a data analyst finds answers to a given set of questions from data.” “A data analyst addresses business problems but a data scientist not just addresses business problems but picks up those problems that will have the most business value once solved.” “Data analysts are the ones who do the day-to-day analysis stuff but data scientists have the what-ifs.”

[@sardarabdullahkhawar8487]

59:00 All clear. Thank you codanics for teaching us all concepts of Data Science with python

[@kumarsagar4491]

09:54 , Example of Statistics , Hypothesis Testing is also part of statistics , agr kisi company me koi machine faulty hai ya nh hai to uski testing bhi hum statistical parameters ki testing kie help se kar sktey hain to ye bhi ek statistics ka example hai

[@ihuzaifahmad]

Thank you codanics for teaching data science with python.

[@alijawad07]

59:51 All clear. Thank you COdanics for teaching us all concepts of Statistics and Data Science with Python.

[@iqramahmood9667]

1:00:02 All clear . Thank you codanics for teaching us all concepts of statistic in data science with python

[@rimshahsabir7394]

14:45 terms used in statistics: sample, population, parameter, statistic, variables, probability, data, alternative hypothesis, analysis of covariance, analysis of variance, average, Coefficient, Confidence intervals, Correlation coefficient

[@armeenasabir2872]

8:17 a data analyst makes sense out of existing data, whereas a data scientist works on new ways of capturing and analyzing data to be used by the analysts. 12:02 Baba g faisalabad 28:30 it was on covid-19 sample dataset

[@bluewater3028]

Dispersion is important and Baba G explanation was simple and to the point.

[@qmtv5772]

All clear, thank you codanics, python

[@iammusman]

All clear_ thankyou codanics for teaching us all the statistics

[@mansoorjan9238]

Thanks codanics for teaching us basic statistics in python.

[@AussieTravels_Vic]

@08:17: Data analyst: deals with analyzing known data using Python, SQL, and R language. They perform daily activities, extract patterns, and identify trends from data. Data scientist: Develop models to deal with the unknown data, with a more extensive scope than a data analyst. Make a framework and algorithm to collect data. Deals with a machine learning algorithm

[@muhammadwaleedanjum7695]

08:19 Data Scientist vs Data Analyst Data Scientist: Works on new ways of Capturing and Analyzing Data to be used by the analysts. Data Analyst: Makes Sense out of existing data. 12:04 Babag faisalabad. 16:23 link nahi aya 18:03 plz irrigation wala likh dain. 28:29 Covid-19 Data, Sample pay tha. 59:47 All clear and thank you codanics for teaching us statistics for Data Science. 1:3:03 lahore gey thay. 1:06:00 victory sign.

[@muhammadowaiskhan4132]

59:49 All clear and Thank you codanics for teaching us all concepts of basisc data science with Python

[@imranpanjwani4514]

Amazing videos i must say, if you know little bit programming , you are in right place to learn data science,

[@hajraanwar8213]

A data scientist is someone who can predict the future based on past patterns and a data analyst is someone who makes sense out of existing data.

[@mh5_4_01]

59:49 / 1:06:08 All clear and thank you codanics for teaching us all types of basic data science.

[@fozailkhan5672]

59:58 All Clear and Thankyou Codanics for Teaching us statistics for data science and basics of data science with python

[@mohsinabbas2246]

25:14 Examples of interval variables include: temperature (Farenheit), temperature (Celcius), pH, SAT score (200-800), credit score (300-850)

[@mumer0101]

12:17 Statistics Terms: Mean Maximum Minimum Percentage Likelihood Variance Correlation Covariance T-Test ANOVA ANCOVA MANOVA MANCOVA

[@Lahori369]

14:54 Mean Median Mode Standards deviation Probability Maximum Minimum Sample population Average Test series Percentage Mean deviation

[@zainshahid798]

15:03 ANOVA t-test chi-square standard daviation variance z-test Null-hypothesis Design of experiments Median Mode Weighted average, etc

[@abdulwaki8590]

Hats off bahi may Allah bless you and Grant you health wealth and success ameen.

[@alihasnain7212]

@8:18 data analyst jo hota hai vo data ko sence deta hai jabke, data scientist hmesha data ko collect b krta hai clean b krta hai, us ki preprocessing se ly kr analysis tk jata or ek data story generate kr leta hai for different purpose

[@usman1694]

All clear, thnks codanics for teaching us data science

[@MujahidAkram]

Liked and Will watch it complete in sha Allah

[@rimshahsabir7394]

25:08: E.g of interval variable. a variable such as annual income that is measured in dollars, and we have three people who make $10,000, $15,000 and $20,000. The second person makes $5,000 more than the first person and $5,000 less than the third person, and the size of these intervals is the same. If there were two other people who make $90,000 and $95,000, the size of that interval between these two people is also the same ($5,000).

[@rimshahsabir7394]

59:57 All clear! Thank you codanics for teaching us basic statistics for data science with python.

[@foziaug12]

25:05 interval variable examples are : temperature (Farenheit), temperature (Celcius), pH, SAT score (200-800), credit score (300-850).

[@islamhussain8026]

# 1:0:00 All clear thank you codanics for teaching us the basic of data science with python

[@salehaattiq1640]

@59:54 All Clear. Thank you codanics for teaching us all concepts of basic data science with python.

[@shahidiqbal0506]

@12:29 Language of statistics: Average, highest, fastest, sab se kam, 40%, kitni ho gi, uper nd nichay, zada and last but not the least > symbol.... These all are related to statistics

[@mh5_4_01]

25:03 / 1:06:08 Examples of interval data includes temperature (in Celsius or Fahrenheit), mark grading, IQ test and CGPA

[@yawarabbas1796]

Like kr dea hy I am going to watch the complete video

[@Lahori369]

59:49 Thanks Codanics, I understand and clear concept with Baba Aammar G

[@zainshahid798]

59:55 All clear. Thank you codanics for teaching us data science

[@Asad.UrRahman]

59:48 all clear thank you Codanics for teaching basic concepts of statistics for data science with python

[@adnankhan-em5um]

i injoy alot sir comdy hy ya lecture great sir

[@wasifmughal4519]

@ 59:57 All clear Thank you Codanics for teaching us a basic concepts of Statistics with Python.

[@hifzaanjum3932]

59:54 , All clear, thank you codanics for teaching us the basic concepts of statistics for data science with python

[@muhammadawais4786]

@59:50 All clear and Thank you codanics for teaching us all concepts of basisc data science. With python

[@tahreemzaheer8994]

28:32 Although sample study is less powerful but to reduce the cost of data collection, covid data was sampled based

[@amnafarooq5871]

8:08 Data analysts typically work with structured data to solve tangible business problems using tools like SQL, R or Python programming languages, data visualization software, and statistical analysis. Data scientists often deal with the unknown by using more advanced data techniques to make predictions about the future.

[@InfobyAR]

8:17 Data Scientist: Works on new ways of Capturing and Analyzing Data to be used by the analysts. Data Analyst: Makes Sense out of existing data.

[@muhammadrizwan688]

@1:00:00 All clear, Thanks codanics for teaching us statistics for data science with Python

[@Oracle_Tech]

All clear thanks Codanics for teaching us basics of data science

[@tahreemzaheer8994]

59:42 all clear thank you codanics for teaching all concepts of statistics and python

[@usahmad8308]

like kar diya... Insha Allah video poori dekhoonga

[@muhammadowaiskhan4132]

25:00 Psychological concepts like intelligence are often quantified through operationalization in tests or inventories. These tests have equal intervals between scores, but they do not have true zeros because they cannot measure “zero intelligence” or “zero personality

[@sultanmuhammad595]

59:49 All clear and thanks codanics for teaching us statistics for data science.

[@sahiljatoi813]

25:07 An interval variable is a one where the difference between two values is meaningful. The difference between a temperature of 100 degrees and 90 degrees is the same difference as between 90 degrees and 80 degrees. A ratio variable, has all the properties of an interval variable, but also has a clear definition of 0.0.

[@Fayez-tk7ph]

59:40, All clear. Thank you codanics for teaching us all concepts of basic Data Science with Python! (laga lein filter)

[@usmankhanjadoon]

Watching again for clearing the basic concepts.

[@kshehzad475]

All clear thank you Codanics for teaching us statistics with Python

[@Sidra_in_Europe]

I'll watch complete video and i have watched previous complete videos

[@adenrajput8531]

10:43 Maximum score Highest speed Lowest runs percentage probability ratio rank

[@nida7825]

#59:45 All clear and thank you for teaching us basic concepts of datascience with codanics and python....

[@lahori_food_maniac]

All crystal clear and thank you codanics for teaching us stats for data science

[@InfobyAR]

15:03 statistics terms are mean,Median, Mode, Inter quartile range , Chi- Square test, Variance, Standard deviation,

[@ymentertainment2349]

#8:10 time pause A data analyst makes sense out of existing data, whereas a data scientist works on new ways of capturing and analyzing data to be used by the analysts.

[@InfobyAR]

59:43 all clear thank you codanics for teching us all concepts of statistics and basic data science with python

[@usahmad8308]

All clear. Thank you Codanics for teaching us all concepts of basic data science statistics Python.

[@kaabrustam3485]

all clear statistics, thanks codanics for teaching it with python

[@Arsalanzeb]

all clear, thank you codanics for teaching us all basics of data science with python

[@farmanullah388]

All clear thank you codanics for teaching us statistics for data science with python

[@Lahori369]

14:53 Mean Median Mode Standards deviation Probability Maximum Minimum Sample population Average Test series Percentage Mean deviation Anova Sample

[@sabamathoor7087]

Liked the video, and will watch it completely and the whole chill inshAllah

[@InfobyAR]

time stemp : 12:27 Average income Highest score cricket Fastest - maximum speed Least number of runs Percentage of teachers Raining prediction Variability Comparison