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6 Reasons To Learn R For Business [2021] Learn R for business - Data science for business is the future of business analytics. Here are 6 reasons why R is the right choice.

This week in #mktgfiasco4000 I read this article www.business-science.io/business/202... which gave some valid reasons on using R for business.

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This week we are beginning our marketing competition and we created our teams of 4 in #mktgfiasco4000. I'm excited to see how this competition goes and hopefully my team wins!

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RPubs - Week 6

rpubs.com/gabrielaaa3/... This is the regression model I used for week 6 in #mktgfiasco4000 !💃

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This week in #mktgfiasco4000 we started using dummy variables in regression models. I am familiar with using excel to create these models but now I am able to do it with R markdown☺️

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This week, I found a textbook that helped me create and interpret many different graphs that will help me with data analysis in R Studio: Practical Data Science with R, Second Edition by Nina Zumel and John Mount. #mktgfiasco4000

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This week, I started my first #datacamp course, Introduction to R. I am learning so many helpful things, from vectors to data frames! #mktgfiasco4000

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I need to learn to not just trust averages. It neeeds to be backed up with a test. Welch’s test reminded me that results can look different by chance, so always check. #mktgfiasco4000

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Boxplots made more sense after practice. 😎 They show not just the average but also how spread out the data is. Ad type 1 had higher sales but more variation. #mktgfiasco4000

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This week I finally understood the difference between t-test and Welch’s t-test. Student’s assumes equal variances, Welch’s doesn’t. Welch is safer in real life since groups usually spread out differently. #mktgfiasco4000 🫡

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After learning about the DataCamp Certificate Courses, I am ready to take the opportunity to learn more foundational skills in the upcoming week. I am keen to explore more of R and possibly Python and even an Intro to AI Agents. #mktgfiasco4000

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Week 4 done and dusted. I was happy to continue my R coding journey with t-tests. Even though Discussion 4 ramped up in difficulty, more experimentation helped me learn and grow. #mktgfiasco4000

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This week centered on t-tests, more specifically Welch's T-Test and A/B Testing. Through the videos and references, I have familiarized myself with the importance of forming effective statistical data analysis and interpreting the results in visual and explanatory means. #mktgfiasco4000

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I'm curious what other things we are going to do with postit and r pubs #mktgfiasco4000

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I discovered that visualizations like ggplot make results clearer.
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I explored descriptive statistics, boxplots, histograms, and performed Welch’s t-tests to compare two groups.
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This week I learned how to use R Studio for statistical analysis and visualization.
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I realized R programming is more powerful than Excel when it comes to handling big datasets. Knowing R can make me stand out in the job market. #mktgfiasco4000

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Boxplots helped me understand sales data in a simple way. I could quickly see which group had higher variation and outliers. Data visualization really makes decision making easier. #mktgfiasco4000

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Learning about A/B testing this week showed me that even when we think we “know” the right answer, data can prove us wrong. Testing is more reliable than assumptions. #mktgfiasco4000

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By examining mean sales and data distribution, I could see that family-themed ads were performing better from the start. This reinforces that combining basic descriptive insights with inferential tests makes for a stronger, more complete conclusion. #mktgfiasco4000

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I learned the importance of combining descriptive analysis with inferential statistics to make business decisions. By running Welch’s t-test, I saw how statistical evidence can confirm which advertisement works better. #mktgfiasco4000

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Through this exercise, I learned that R programming allows me to analyze data more effectively than Excel alone. I understood the process of hypothesis testing, from checking assumptions to drawing conclusions. #mktgfiasco4000

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From this exercise, I learned how to apply Welch’s t-test to compare two groups with unequal variance. Using R and real data helped me see why p-values matter in decision-making. #mktgfiasco4000

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I learned how to quickly extract and condense information from different sources, from articles to videos.💡 Looking forward, I'm excited to refine my ability to explain advanced data concepts in a clear, relatable way.
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This experience improved my ability to synthesize complex topics into concise summaries. I want to learn more about translating advanced data visualization and statistical concepts from R programming into more intuitive, everyday language.

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This week I also learned how histograms help show the distribution of sales data. Unlike Boxplots, they give a clearer picture of how values are spread across ranges. Seeing the shape of the data made it easier to understand patterns and compare groups visually. #mktgfiasco4000

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Boxplots turned out to be a simple but powerful tool. They show differences between groups quickly, making it easier to spot trends in sales data. I like how visuals and statistics work together. It made me realize how important it is to combine numbers with pictures. #mktgfiasco4000

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This week I learned how Welch's t-test helps when two groups have different variances, making it more reliable than the standard t-test. It was eye-opening to see how this applies in marketing, where real data is rarely perfect. Statistics really guides smarter decisions. #mktgfiasco4000

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A/B Testing: Test Your Own Hypotheses & Prepare to be Wrong - Stuart Frisby
A/B Testing: Test Your Own Hypotheses & Prepare to be Wrong - Stuart Frisby YouTube video by O'Reilly

Our professor required us to watch this video on A/B Testing. I liked the message that the failures of your hypothesis will help you learn and succeed. This is a great takeaway from this video! youtu.be/VQpQ0YHSfqM?... #mktgfiasco4000

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Week 4 update in #mktgfiasco4000 : Using R to create a t-test is way easier than Excel 👁️👄👁️. I'm surprised because I've only ever used Excel, but still getting used to R, so knock on wood.

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