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Tech Classes
Индия
Добавлен 12 июн 2020
On my channel (Tech Classes), you can find tutorials on technical topics related to python, data science, machine learning and many more.
White Noise | Random Walk | Ljung Box Test | Time Series Analysis | Part 8
This video is a part 8 of the complete Time Series Analysis Playlist for Data Analysts and Data Scientists and covers following topics:
1. White Noise and its properties
2. Random Walk and its properties
3. Ljung Box Test and its Python implementation
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Follow me on:
✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174
✅Instagram: techie.data
🔥 Book 1:1 call with me (Career Guidance, Resume Review, LinkedIn Profile Review) : topmate.io/ayushi_mishra/133733
Other Useful Videos:
Data Analyst Roadmap: ruclips.net/video/MKncxvvRJXM/видео.html
Data Analysis Project using Python: ruclips.net/video/obJZ1rB7TKc/видео.html
Python vs R: Which is best for career? : ruclips.net/vid...
1. White Noise and its properties
2. Random Walk and its properties
3. Ljung Box Test and its Python implementation
➖➖➖➖➖➖➖➖➖➖➖➖➖
Follow me on:
✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174
✅Instagram: techie.data
🔥 Book 1:1 call with me (Career Guidance, Resume Review, LinkedIn Profile Review) : topmate.io/ayushi_mishra/133733
Other Useful Videos:
Data Analyst Roadmap: ruclips.net/video/MKncxvvRJXM/видео.html
Data Analysis Project using Python: ruclips.net/video/obJZ1rB7TKc/видео.html
Python vs R: Which is best for career? : ruclips.net/vid...
Просмотров: 142
Видео
Making Time Series Data, Stationary | Differencing | Transformation | Detrending | Part 7 | Python
Просмотров 23112 часов назад
This video is a part 7 of the complete Time Series Analysis Playlist for Data Analysts and Data Scientists and covers following topics: 1. Different methods to make a time series data stationary 2. Differencing (First order differencing and Second order differencing) 3. Transformation (Logarithmic, Power and BoxCox transformation) 4. Detrending 5. Seasonal Adjustments ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on...
ADF | KPSS | KS Tests | Stationarity Tests in Time Series Analysis | Part 6 | Python
Просмотров 47421 день назад
This video is a part 6 of the complete Time Series Analysis Playlist for Data Analysts and Data Scientists and covers following topics: 1. Stationarity Tests 2. Augmented Dickey Fuller (ADF) Test 3. Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test 4. Kolmogorov-Smirnov (K-S) test 5. Python Implementation ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram:...
Stationarity in Time Series Analysis | Weak and Strict Stationarity | Part 5
Просмотров 527Месяц назад
This video is a part 5 of the complete Time Series Analysis Playlist for Data Analysts and Data Scientists and covers following topics: 1. Stationarity 2. Why do we need stationarity? 3. Understanding stationarity using different charts examples 4. Weak Stationarity 5. Strict Stationarity ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram: instagram.co...
STL Decomposition using LOESS | Time Series Decomposition | Time Series Analysis | Part 4
Просмотров 392Месяц назад
This video is a part 4 of the complete Time Series Analysis Playlist for Data Analysts and Data Scientists and covers following topics: 1. STL Decomposition 2. LOESS Method 3. Python implementation of STL Time Series Decomposition 4. Difference between STL and Classical ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram: techie.data 🔥 Bo...
Classical Time Series Decomposition | Additive | Multiplicative | Trend | Seasonality | Residual
Просмотров 428Месяц назад
This video is a part 3 of the complete Time Series Analysis Playlist for Data Analysts and Data Scientists and covers following topics: 1. Time Series Decomposition 2. Trend, Seasonality, Cycles, Residual 3. Python implementation of Classical Time Series Decomposition 4. Additive and Multiplicative model ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagr...
Time Series Data | Time Series Analysis | Data Analysts | Data Scientists | Part 2
Просмотров 971Месяц назад
This video is a part 2 of the complete Time Series Analysis Playlist for Data Analysts and Data Scientists and covers following topics: 1. What is time series data? 2. Key characteristics of time series data 3. What is time series analysis? 4. Goals of time series analysis 5. Why we do time series analysis 6. Importance of time series analysis ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin...
Time Series Analysis for Data Analysts | Data Scientists | Complete Syllabus | Part 1
Просмотров 2,4 тыс.Месяц назад
In this video, we present the complete syllabus for our "Time Series Analysis for Data Analysts and Data Scientists" course. Whether you're a data enthusiast, student, or professional looking to sharpen your time series skills, this syllabus overview will give you a sneak peek into what you can expect from our comprehensive course. 🔴 Stay tuned to master the Time Series Analysis. Don't forget t...
Chi Square Test | Test for Independence | Goodness of Fit Test | Statistics Tutorial
Просмотров 1,3 тыс.2 месяца назад
This video covers the following: 1. What is Chi Square test? 2. When and where Chi Square test can be used? 3. Chi Square Test for Independence 4. Chi Square Goodness of Fit Test ➖➖➖➖➖➖➖➖➖➖➖➖➖ 💡 Complete Statistics eBook (Written by me covering all topics): topmate.io/ayushi_mishra/865848 👍 Subscribe for more Data Science content: bit.ly/48MFgCf ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linked...
ANOVA Test | F Statistics | One Way ANOVA | Two Way ANOV | Statistics Tutorial
Просмотров 1,2 тыс.2 месяца назад
This video covers the following: 1. ANOVA Test 2. F Statistics 3. When and where ANOVA can be used? 4. One Way ANOVA 5. Two Way ANOVA ➖➖➖➖➖➖➖➖➖➖➖➖➖ 💡 Complete Statistics eBook (Written by me covering all topics): topmate.io/ayushi_mishra/865848 👍 Subscribe for more Data Science content: bit.ly/48MFgCf ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram:...
T Test Hypothesis Testing | Independent and Paired T Test | Statistics Tutorial
Просмотров 3,7 тыс.3 месяца назад
This video covers the following: 1. T Test 2. When and where t test can be used? 3. Independent t test 4. Paired t test 5. Detailed explanation with example ➖➖➖➖➖➖➖➖➖➖➖➖➖ 💡 Complete Statistics eBook (Written by me covering all topics): topmate.io/ayushi_mishra/865848 👍 Subscribe for more Data Science content: bit.ly/48MFgCf ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishr...
Z Test hypothesis Testing | Types of Z Test | Explanation with example | Statistics
Просмотров 2,2 тыс.3 месяца назад
This video covers the following: 1. Z Test 2. When and where z test can be used? 3. One sample Z test 4. Two sample z test 5. Example ➖➖➖➖➖➖➖➖➖➖➖➖➖ 💡 Complete Statistics eBook (Written by me covering all topics): topmate.io/ayushi_mishra/865848 👍 Subscribe for more Data Science content: bit.ly/48MFgCf ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram:...
One tailed and Two tailed Tests | Hypothesis Testing | Detailed Explanation with Example
Просмотров 3 тыс.3 месяца назад
This video covers the following: 1. One tailed test 2. Two tailed test 3. When to use them 4. In depth explanation of both tests with example ➖➖➖➖➖➖➖➖➖➖➖➖➖ 💡 Complete Statistics eBook (Written by me covering all topics): topmate.io/ayushi_mishra/865848 👍 Subscribe for more Data Science content: bit.ly/48MFgCf ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅In...
Type 1 and Type 2 Error | Hypothesis Error | Statistics Error
Просмотров 1,6 тыс.3 месяца назад
This video covers the following: 1. Type1 error 2. Type 2 error 3. In depth explanation of both errors with example ➖➖➖➖➖➖➖➖➖➖➖➖➖ 💡 Complete Statistics eBook (Written by me covering all topics): topmate.io/ayushi_mishra/865848 👍 Subscribe for more Data Science content: bit.ly/48MFgCf ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram: tec...
Hypothesis Testing| Null and Alternate Hypothesis | Level of Significance | P Value | Statistics
Просмотров 2,2 тыс.3 месяца назад
This video covers the following: 1. Hypothesis Testing 2. Null and Alternate Hypothesis 3. Level of Significance 4. P value ➖➖➖➖➖➖➖➖➖➖➖➖➖ 💡 Complete Statistics eBook (Written by me covering all topics): topmate.io/ayushi_mishra/865848 👍 Subscribe for more Data Science content: bit.ly/48MFgCf ➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow me on: ✅LinkedIn: www.linkedin.com/in/ayushi-mishra-30813b174 ✅Instagram: instagram...
Student's T Distribution | Z Distribution | T test | Statistics Tutorial
Просмотров 1,5 тыс.3 месяца назад
Student's T Distribution | Z Distribution | T test | Statistics Tutorial
A/B Testing & Regression Analysis Project | Marketing Campaign Analysis | Data Analysis Project
Просмотров 4,9 тыс.4 месяца назад
A/B Testing & Regression Analysis Project | Marketing Campaign Analysis | Data Analysis Project
Impact of AI on Data Analyst Jobs | Future of Data Analyst Jobs | Will AI Replace Data Analysts?
Просмотров 2,5 тыс.4 месяца назад
Impact of AI on Data Analyst Jobs | Future of Data Analyst Jobs | Will AI Replace Data Analysts?
Confidence Interval | Interval Estimation | Margin of Error | Statistics Tutorial
Просмотров 1,9 тыс.4 месяца назад
Confidence Interval | Interval Estimation | Margin of Error | Statistics Tutorial
Inferential Statistics | Point Estimation | Interval Estimation | Statistics Tutorial
Просмотров 2,7 тыс.4 месяца назад
Inferential Statistics | Point Estimation | Interval Estimation | Statistics Tutorial
Empirical Rule | 68-95-99.7 Rule | Normal Distributions | Statistics Tutorial
Просмотров 1,7 тыс.4 месяца назад
Empirical Rule | 68-95-99.7 Rule | Normal Distributions | Statistics Tutorial
SQL Project For Data Analytics | SQL Portfolio Project | Business Problem | Report Making
Просмотров 56 тыс.4 месяца назад
SQL Project For Data Analytics | SQL Portfolio Project | Business Problem | Report Making
Standardisation | Normalisation | Probability Distributions | Feature Scaling
Просмотров 2,1 тыс.4 месяца назад
Standardisation | Normalisation | Probability Distributions | Feature Scaling
Normal Distributions | Standard Normal Distributions | Z Distributions | Z Score
Просмотров 1,9 тыс.4 месяца назад
Normal Distributions | Standard Normal Distributions | Z Distributions | Z Score
Uniform Distribution | Continuous Distribution | Statistics Tutorial | Probability Distribution
Просмотров 1,7 тыс.4 месяца назад
Uniform Distribution | Continuous Distribution | Statistics Tutorial | Probability Distribution
Bernoulli Distributions | Binomial Distributions | Discrete Probability Distributions
Просмотров 2,4 тыс.5 месяцев назад
Bernoulli Distributions | Binomial Distributions | Discrete Probability Distributions
PMF | PDF | Probability Distributions | Probability Mass Function | Probability Density Function
Просмотров 2,8 тыс.5 месяцев назад
PMF | PDF | Probability Distributions | Probability Mass Function | Probability Density Function
HUGE MISTAKE ❌ Choosing WRONG Educational Path | Degree vs Bootcamps | 🤔 Which Is Really WORTH It?
Просмотров 1 тыс.5 месяцев назад
HUGE MISTAKE ❌ Choosing WRONG Educational Path | Degree vs Bootcamps | 🤔 Which Is Really WORTH It?
Statistics Project On Hypothesis Testing You NEED In Your Portfolio | Data Analysis Project
Просмотров 22 тыс.5 месяцев назад
Statistics Project On Hypothesis Testing You NEED In Your Portfolio | Data Analysis Project
Bayes Theorem | Conditional Probability | Statistics Tutorial
Просмотров 3 тыс.5 месяцев назад
Bayes Theorem | Conditional Probability | Statistics Tutorial
48.29
Sorry nahi samajh aa raha hai
very nice
Thank you ma'am ❤
very nice mam
Qith lot of respect. you did lot of mistakes, which lead to confusions for example on 2:58:45 you said z score for 95% is 1.96. but actually it is 1.64 and it is 1.96 for 97.5%. Please try to correct with hints.
00:00 Syllabus 4:16: Introduction to Statistics 6:39: Descriptive Statistics 9:16: Inferential Statistics 12:45: Types of Data and Variables 21:29: Population and Sample 25:40: Sampling Techniques 33:34: Statistical Analysis 38:12: Measures of Central Tendency 48:18: Measures of Dispersion 1:01:17: Frequency | Relative and Cumulative 1:07:38: Statistical Visualisation 1:25:16: Outliers 1:29:45: Covariance | Correlation | Causation 1:38:56: Probability Concepts (Sample Space | Random Experiment | Event | Complement of Probability) 1:46:24: Types of Events 1:55:30: Conditional Probability 1:58:14: Bayes Theorem 2:06:05: Probability mass function and Probability density function 2:12:20: Bernoulli Distribution | Binomial Distribution 2:19:13: Uniform Distribution 2:22:56: Normal Distribution | Z Distribution 2:27:52: Standardisation | Normalisation 2:36:06: Empirical Rule 2:40:11: Inferential Statistics 2:42:02: Point and Interval Estimation 2:51:30: Confidence Interval 2:59:40: T distribution 3:03:13: Hypothesis Testing 3:06:23: Null and Alternate Hypothesis 3:09:29: Level of Significance | P value 3:12:51: Type | and Type || Error 3:16:29: One tailed and Two tailed Test 3:19:20: Z Test (One sample z test | two sample z test) 3:24:35: T Test (Independent sample t test | Paired sample t test) 3:28:45: ANOVA Test (One way ANOVA | Two way ANOVA) 3:38:26: Chi-Square Test (Independence | Goodness of Fit Test)
provide notes pdf , ppt
Koi bta sakta hai ki ye Excel ke kis version me bna hai 2013 yah us se uper
In resume, What should I write for this project can you please explain in bullet points
you are looking wonderful
Ye SQL project kaha hai ye to python hai in coding
@@fashion_queen companies work on project like this and want to see this kind of project
1:28:37 - Q3 formula is wrong It should be Q3 + 1.5*IQR that is upper limit of box plot
Thank you for the playlist🤗
Thanks for providing such deep knowledge for free.❤
Brilliantly explained! hats off to you Ma'm!
Thanks mam.. ❤
getting this error while changing " df['reservation_status_date'] = pd.to_datetime(df['reservation_status_date']) " to the datetime : ValueError: time data "22/4/2015" doesn't match format "%m/%d/%Y", at position 4. You might want to try: - passing `format` if your strings have a consistent format; - passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format; - passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this. Can you please tell me what to do ??
Thank you
Very informative 😊
Problem statement client ke dwara di jati hogi ?
Ma'am! Could you please create a complete Data Science course for us ?
Why is age not ordinal variable and why rating isn't numerical variable.?
Thanks a lot
Very Nice Lecture
can u continue the series ....?
Mam excel basic se pdaya nai
CANNOT DOWNLOAD EBOOK
Really amazing 👍👍 , thank you 🙏
Isko resume mai add kr sakte hai
4:13 introduction to statistics
Hello
Truly valuable content and most honest data analyst coach on youtube . better than a lot of top channels who make videos on data analysis.
It will be great if you make a separate video for data analyst only . This will help them to just focus on that particular video or video series and crack the interview . It will help them to save their time and just focusing on that particular video for statistics . Thanks for the video 🤍
Part 3 is not uploaded, traditional decomposition method. Kindly upload it
T distribution is used when Sigma is not known and Z distribution is used when Sigma is known. Please try to provide correct knowledge. Z distribution can be used with sample size of 30 or less also because of CLT (central limit theorem)
Excel ki full playlist bna kr daal dein
I hop you Will make English version
I wish it was in English it's sounds you explain everything Easy
Superb
Legend here 😂
How is 360digitmg inst
PLEASE LET US KNOW ABOUT YOUR WORK PROFILE I.E. ROLES N REPOSNB'Y IN JIO.
can you tell me how you have performed the action for doing a project in jupyter book? Because I am not able to do it.
No csnt
Mam ma tutison kabhi nhi jata hu agar app hamara tutison padata to ma rose jati 😭😭😭
Thanks
Thanks
Thanks
Thank you