#Null Hypothesis

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#Null Hypothesis Reel by @chithappens.co - Null Hypothesis (H₀): This is the default assumption that there is no effect or no relationship between variables. It's what we test against. Think: "
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@chithappens.co
Null Hypothesis (H₀): This is the default assumption that there is no effect or no relationship between variables. It’s what we test against. Think: “Nothing’s happening here!” Alternate Hypothesis (H₁): This is what we propose when we believe there’s an effect or relationship. It’s the claim we’re trying to prove. Think: “Something’s definitely happening! #simplystatistics #psychology #research #psychologyfacts #nullhypothesis #alternatehypothesis #research #dissertation #chithappens
#Null Hypothesis Reel by @hit_the_tuan - When the p is low, reject that H0 #statstok #nullhypothesis #hypthesistesting #statistics #mathstok #average #statsmemes #varsitymemes #womeninstem
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@hit_the_tuan
When the p is low, reject that H0 #statstok #nullhypothesis #hypthesistesting #statistics #mathstok #average #statsmemes #varsitymemes #womeninstem
#Null Hypothesis Reel by @tanveennnn - econometrics coded these days 📑📊👩‍💻 . . . . . . . #econometrics #statistics #nasty #nullhypothesis #internationalstudents #fyp #explorepage #trend
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@tanveennnn
econometrics coded these days 📑📊👩‍💻 . . . . . . . #econometrics #statistics #nasty #nullhypothesis #internationalstudents #fyp #explorepage #trending
#Null Hypothesis Reel by @tech_jroshan - 🎯 Hypothesis Testing in Data Science - A Must-Know Skill! 📊 Whether you're analyzing experiments, comparing A/B test results, or validating assumpt
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@tech_jroshan
🎯 Hypothesis Testing in Data Science – A Must-Know Skill! 📊 Whether you're analyzing experiments, comparing A/B test results, or validating assumptions in machine learning — hypothesis testing is foundational to sound decision-making. Here's a quick breakdown of the most common types of hypothesis tests every analyst and data scientist should know: 🔍 Common Types of Hypothesis Testing 1️⃣ Z-Test ✔️ Used when population variance is known and sample size is large (n greator than 30) 📌 Example: Testing average delivery times of a logistics company vs. claimed value. 2️⃣ T-Test ✔️ Used when population variance is unknown or sample size is small One-sample t-test: Compare sample mean to population mean Two-sample t-test: Compare means of two independent samples Paired t-test: Compare means from the same group at two different times 3️⃣ Chi-Square Test ✔️ Used for categorical data Goodness of Fit: Is observed distribution different from expected? Test of Independence: Are two categorical variables related? 4️⃣ ANOVA (Analysis of Variance) ✔️ Compares means across 3 or more groups 📌 Example: Comparing test scores across multiple classrooms or products. 💡 When to Use What? Parametric tests: Use when data is normally distributed Non-parametric tests: Use when data is skewed or ordinal 📈 Key Concepts to Remember: Null hypothesis (H₀): The status quo or no effect Alternative hypothesis (H₁): What you’re testing for p-value: Probability of observing your results if H₀ is true Significance level (α): Typically 0.05 #HypothesisTesting #DataScience #Statistics #ABTesting #Analytics #Python #MachineLearning #BusinessIntelligence #DataDriven #problemsolvingskills #CareerGrowth #Analytics #pvalue #tTest #ChiSquare #ZTest #ANOVA
#Null Hypothesis Reel by @psych.with.dee - A p value tells us how likely it is that our results happened just by chance. The null hypothesis functions as a reversal or negation of the research
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@psych.with.dee
A p value tells us how likely it is that our results happened just by chance. The null hypothesis functions as a reversal or negation of the research hypothesis. The researcher either rejects or fails to reject the null hypothesis, but never accept the null hypothesis. The entire goal of the research becomes to verify and reject the null hypothesis and in turn accept the alternative hypothesis. When p<0.05, the result is statistically significant. This means the data provides strong evidence to reject the null hypothesis. It simply means that the result is very unlikely to be due to chance, so something real is happening. For example, if p=0.01, it means there is only 1% chance that this result happened randomly. Hence, there is a strong evidence against the null hypothesis. Thus, we reject the null hypothesis and accept the alternative hypothesis. When p>0.05, the result is not statistically significant. This means the data does not provide strong enough evidence to reject the null hypothesis. For example, if p=0.50, it means that there is a 50% chance that this result happened randomly. The observed effect could be due to chance, but this does not mean the effect doesn’t exist, only that the study wasn’t convincing enough to demonstrate it. The evidence to reject the null hypothesis is weak and hence we fail to reject the null hypothesis. Remember, we never accept the null hypothesis. [ statistics, psychology, null hypothesis, alternative hypothesis, research, p value, type I error, type II error, false positive, false negative, significance level, error, result, statistically significant, chance, random, weak evidence, strong evidence, accept, reject, fail to reject, research hypothesis, hypothesis, low p value, high p value, trending audio, relatable, viral, fyp, reels, instagram, stats, reel it feel it, trending reels ] #relatable #statistics #psychology #viral #research
#Null Hypothesis Reel by @justtscroollll - Reject them the way companies reject your cv's 😂 #trend #fypp #fyp #viral #viralreels #pvalue #nullhypothesis #reject
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@justtscroollll
Reject them the way companies reject your cv’s 😂 #trend #fypp #fyp #viral #viralreels #pvalue #nullhypothesis #reject
#Null Hypothesis Reel by @chithappens.co - A p-value, or probability value, is a statistical measurement that indicates how likely it is that a set of data could have occurred under a null hypo
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@chithappens.co
A p-value, or probability value, is a statistical measurement that indicates how likely it is that a set of data could have occurred under a null hypothesis What it measures The probability that the observed results could have occurred if the null hypothesis were true What it indicates A smaller p-value indicates greater statistical incompatibility between the data and the null hypothesis #simplystatistics #psychology #research #statistics #dissertation #psychmajor #mapsychology #pvalue #psychologyfacts
#Null Hypothesis Reel by @_knightofsteel (verified account) - Most of my followers either got this wrong or refused to answer the question. We don't accept the null hypothesis in any circumstances. We either fail
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@_knightofsteel
Most of my followers either got this wrong or refused to answer the question. We don't accept the null hypothesis in any circumstances. We either fail to reject or retain if we cannot reject it. References below: Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49(12), 997–1003. https://doi.org/10.1037/0003-066X.49.12.997Fisher, R. A. (1935). The design of experiments. Oliver & Boyd.Neyman, J., & Pearson, E. S. (1933). On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 231(694–706), 289–337. https://doi.org/10.1098/rsta.1933.0009 . . . . #statistics #research #psychology #knightofsteel
#Null Hypothesis Reel by @apbiopenguins - ✨AP Bio Tips & Tricks: Null Hypothesis✨ #apbio #apbiology #studywithme #apexams #highschool
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@apbiopenguins
✨AP Bio Tips & Tricks: Null Hypothesis✨ #apbio #apbiology #studywithme #apexams #highschool
#Null Hypothesis Reel by @ahyderabadiinusa - When the p-value is less than 0.05, and you know what that means. There I was, staring at my statistical analysis output, rereading the regression tab
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@ahyderabadiinusa
When the p-value is less than 0.05, and you know what that means. There I was, staring at my statistical analysis output, rereading the regression table, checking the research methodology, making sure the data analysis was correct. The moment every PhD student and graduate student waits for — statistical significance. Reject the null hypothesis. This is the real graduate school experience — research design, hypothesis testing, quantitative research, statistical analysis, and academic writing that define doctoral training and higher education. Moments like this remind you why research matters. As a woman in STEM and an international student navigating academia, these small wins in dissertation research, data analysis, and scholarly work build confidence and resilience. PhD life. Graduate school. Women in STEM. Academic journey. International student. Higher education. Doctoral journey. 🕊️🧕🏻 study abroad, international student, PhD journey, master’s abroad, student life in the USA, academic journey, research life, women in education, chasing dreams, growth phase, learning and growing, Keywords, becoming her, student journey, work, goals, memories, PhD life, PhD student, study, grad life, master’s abroad, study abroad life, international student journey, academic goals, growth, mindset, resilience, becoming her, dream life, that girl, studying, hard work, women in stem, university, grad school, #studystudystudy #phdlife #studyroutine #gradstudent #usa
#Null Hypothesis Reel by @thesoulvia - A p-value tells us how likely it is that our results happened just by chance. When p > 0.05, the result is not statistically significant. This means
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@thesoulvia
A p-value tells us how likely it is that our results happened just by chance. When p > 0.05, the result is not statistically significant. This means the data does not provide strong enough evidence to reject the null hypothesis. The observed effect could be due to chance, but this does not mean the effect doesn’t exist, only that the study wasn’t convincing enough to demonstrate it. Important: it does not prove that nothing is happening. It only tells us that the data isn’t convincing enough yet. #psychology #trendingnow #college #fyp #viralvideos

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