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vaitybharati /Assignment-04-Simple-Linear-Regression-2

Star9

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis t-score model-testing distplot regression-plot r-square-values

UpdatedMay 30, 2021
Jupyter Notebook

vaitybharati /Assignment-1-Q24-Basic-Statistics-Level-1-

Star5

Q 24) A Government company claims that an average light bulb lasts 270 days. A researcher randomly selects 18 bulbs for testing. The sampled bulbs last an average of 260 days, with a standard deviation of 90 days. If the CEO's claim were true, what is the probability that 18 randomly selected bulbs would have an average life of no more than 260 …

python stats scipy cdf hypothesis-testing t-score

UpdatedMar 22, 2021
Jupyter Notebook

vaitybharati /Assignment-1-Q23-Basic-Statistics-Level-1-

Star3

Q 23) Calculate the t scores of 95% confidence interval, 96% confidence interval, 99% confidence interval for sample size of 25

python stats scipy confidence-intervals t-score ppf

UpdatedMar 20, 2021
Jupyter Notebook

vaitybharati /Assignment-04-Simple-Linear-Regression-1

Star3

Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Mo…

python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis rsquare-values t-score model-testing distplot regression-plot

UpdatedMay 29, 2021
Jupyter Notebook

vaitybharati /P25.-Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data

Star2

Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.

visualization python smf eda pandas seaborn p-value model-predictions goodness-of-fit ols-regression statsmodels simple-linear-regression correlation-analysis t-score distplot determination-coefficient r-square-values regplot

UpdatedJun 9, 2021
Jupyter Notebook

reshma78611 /Basic-stats-in-R-language

Star2

Basic Statistic operations using R language

probability dispersion visualizations normal-distribution z-score confidence-interval skewness kurtosis t-score central-tendency

UpdatedFeb 10, 2021
R

vaitybharati /P19.-Hypothesis-Testing-2-Proportion-T-test-Students-Jobs-in-2-States-

Star1

Hypothesis-Testing-2-Proportion-T-test-Students-Jobs-in-2-States. Assume Null Hypothesis as Ho is p1-p2 = 0 i.e. p1 ≠ p2. Thus Alternate Hypthesis as Ha is p1 = p2. Explanation of bernoulli Binomial RV: np.random.binomial(n=1,p,size) Suppose you perform an experiment with two possible outcomes: either success or failure. Success happens with pro…

python numpy probability pandas p-value hypothesis-testing statsmodels degrees-of-freedom significance-testing null-hypothesis t-score alternate-hypothesis proportion-test 2-proportion-ttest bernoulli-binomial-rv

UpdatedMay 20, 2021
Jupyter Notebook

CS-LEE2022 /Test_a_Perceptual_Phenomenon

Star1

Use descriptive statistics to describe qualities of a sample, set up a hypothesis test, make inferences from a sample, and draw conclusions based on the results.

data-science csv numpy pandas data-visualization matplotlib inferential-statistics descriptive-statistics udacity-data-analyst-nanodegree stroop-effect z-score perceptual-phenomenon null-hypothesis alternative-hypothesis congruent incongruent t-score type1-error

UpdatedJan 10, 2019
HTML

vaitybharati /P17.-Hypothesis-Testing-1-Sample-1-Tail-Test-Salmonella-Outbreak-

Star1

Hypothesis-Testing-1-Sample-1-Tail-Test-Salmonella-Outbreak. 1-sample 1-tail ttest. Assume Null Hypothesis Ho as Mean Salmonella <= 0.3. Thus Alternate Hypothesis Ha as Mean Salmonella > 0.3. As No direct code for 1-sample 1-tail ttest available with unknown SD and arrays of means. Hence we find probability using 1-sample 2-tail ttest and divide…

python numpy array pandas p-value stats scipy hypothesis-testing one-sample-t-test significance-testing null-hypothesis t-score alternate-hypothesis one-tail-test two-tail-test

UpdatedMay 4, 2021
Jupyter Notebook

vaitybharati /P26.-Supervised-ML---Multiple-Linear-Regression---Cars-dataset

Star1

Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Levera…

python eda scatter-plot ols-regression statsmodels aic correlation-analysis collinearity-diagnostics heteroscedasticity p-values vif t-score multi-linear-regression residual-analysis cooks-distance r-square-values influence-plot homoscedasticity leverage-value

UpdatedJun 13, 2021
Jupyter Notebook

vaitybharati /P18.-Hypothesis-Testing-2-Sample-2-Tail-Test-Drugs-and-Placebos-

Star1

Hypothesis-Testing-2-Sample-2-Tail-Test-Drugs-and-Placebos. Note: This python code states both 2-sample 1-tail and 2-sample 2-tail codes. Treatment group mean is Mu1 Contrl group mean is Mu2 2-sample 2-tail ttest Assume Null Hypothesis Ho as Mu1 = Mu2 Thus Alternate Hypothesis Ha as Mu1 ≠ Mu2.

python numpy pandas p-value stats scipy hypothesis-testing independent-variables two-sample-t-test significance-testing null-hypothesis t-score alternate-hypothesis

UpdatedMay 19, 2021
Jupyter Notebook

vaitybharati /P15.-Hypothesis-Testing-1S1T---Super-Market-Loyality-Program

Star1

Hypothesis-Testing 1S1T-Super-Market-Loyality-Program. Population Parameters: Mean=120 Sample Parameters: n=80, Mean=130, SD=40, df=80-1=79

python p-value stats scipy hypothesis-testing norm one-sample-t-test significance-testing t-score

UpdatedApr 25, 2021
Jupyter Notebook

vaitybharati /P13.-C.I.E-using-t-values-Confidence-Interval-Estimate-

Star1

credit card launch example sample mean: 1990 sample SD: 2833 Pop mean: ? n=140 (In cases, where pop SD is not known, use t-values and practically in all problems prefer t over z) Q: Construct 95% confidence interval for mean card balance and interpret it

python numpy mean pandas stats scipy confidence-intervals standard-deviation t-score ppf standard-error

UpdatedApr 16, 2021
Jupyter Notebook

vaitybharati /P16.-Hypothesis-Testing-1S2T---Call-Center-Process

Star1

Hypothesis Testing 1S2T - Call Center Process. Sample Parameters: n=50, df=50-1=49, Mean1=4, SD1=3 1-sample 2-tail ttest Assume Null Hypothesis Ho as Mean1 = 4 Thus, Alternate Hypothesis Ha as Mean1 ≠ 4

python mean p-value stats scipy hypothesis-testing norm standard-deviation one-sample-t-test null-hypothesis t-score alternate-hypothesis two-tail-test

UpdatedMay 3, 2021
Jupyter Notebook

reshma78611 /Basic-stats-using-Python

Star0

Basic Statistic operations using Python

probability dispersion visualizations normal-distribution z-score confidence-interval skewness kurtosis t-score central-tendency

UpdatedFeb 10, 2021
Python

PatilSukanya /Assignment-04.-Simple-Linear-Regression-Q1

Star0

Used libraries and functions as follows:

python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression model-building simple-linear-regression correlation-analysis t-score model-testing distplot statmodels regression-plot r-square-values

UpdatedSep 12, 2022
Jupyter Notebook

shwetapardhi /Assignment-04-Simple-Linear-Regression-1

Star0

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi