Linearregression Study guides, Class notes & Summaries
Looking for the best study guides, study notes and summaries about Linearregression? On this page you'll find 13 study documents about Linearregression.
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Spreadsheets_for_Business_Analytics_Week14_LinearRegression
- Exam (elaborations) • 2 pages • 2024
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Linear Regression 
Open the attached .csv file. 
Select Regression from the data analysis tab 
Weight will be our predictor variable and MPG the response variable. Select your x (predictor) and y (response) ranges accordingly. Check the labels button and and output cell. 
Observe the ANOVA matrix. The F-statistic will tell you whether your model is better than simply using the mean. You will want the F-statistic to be as high as possible and the significance to be as low as possible. 
The equati...
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Econometrics Summary_All Lecture Topics (MT and LT)
- Summary • 25 pages • 2022
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This summary contains key takeaways, main ideas and concepts, formulas from each of the topics covered throughout the year (both Michaelmas and Lent Terms). The following summary gives an overall view of the MG205 Econometrics course, as well as a solid base for exam revisions allowing you to consolidate your knowledge without going over...AGAIN... a thousand slides provided by the teacher. 
The topics summarised are: 
The Linear Regression Model, MultipleRegression, Inference, Functional Form, ...
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DATA SCIEN 2020Machine Learning Project
- Presentation • 72 pages • 2023
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In [1]: import pandas as pd 
import numpy as np 
from sklearn import preprocessing 
from _selection import train_test_split 
from _bayes import GaussianNB 
from cs import accuracy_score 
import seaborn as sns 
import t as plt 
from import zscore 
import warnings 
rwarnings( "ignore") 
from r_model import LinearRegression 
from er import KMeans 
from cs import mean_squared_error 
from ers_influence import variance_inflation_fac 
tor 
import math 
from r_model import LogisticRegression 
from sk...
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DATA SCIEN 2020Predictive Modeling Project
- Presentation • 82 pages • 2023
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- $8.99
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In [205]: from ets import load_boston 
import pandas as pd 
import numpy as np 
import seaborn as sns 
import t as plt 
import as sm 
from _selection import train_test_split 
from r_model import LinearRegression 
from er import KMeans 
from cs import mean_squared_error 
from ers_influence import variance_inflation_fac 
tor 
import math 
1.1. Read the data and do exploratory data analysis. Describe the data 
briefly. (Check the null values, Data types, shape, EDA). Perform 
Univariate and Bivari...
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DATA SCIEN Machine Learning Project.html
- Exam (elaborations) • 72 pages • 2023
-
- $9.49
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In [1]: import pandas as pd 
import numpy as np 
from sklearn import preprocessing 
from _selection import train_test_split 
from _bayes import GaussianNB 
from cs import accuracy_score 
import seaborn as sns 
import t as plt 
from import zscore 
import warnings 
rwarnings( "ignore") 
from r_model import LinearRegression 
from er import KMeans 
from cs import mean_squared_error 
from ers_influence import variance_inflation_fac 
tor 
import math 
from r_model import LogisticRegression 
from sk...
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Data science >Machine Learning Project.html.2023& study guide with complete solution
- Other • 72 pages • 2023
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- $10.49
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import pandas as pd 
import numpy as np 
from sklearn import preprocessing 
from _selection import train_test_split 
from _bayes import GaussianNB 
from cs import accuracy_score 
import seaborn as sns 
import t as plt 
from import zscore 
import warnings 
rwarnings( "ignore") 
from r_model import LinearRegression 
from er import KMeans 
from cs import mean_squared_error 
from ers_influence import variance_inflation_fac 
tor 
import math 
from r_model import LogisticRegression 
from sklearn im...
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Linear Regression & Logistic Regression.
- Exam (elaborations) • 12 pages • 2022
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- $10.49
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DATA SCIEN Predictive Modeling Project.html.
- Exam (elaborations) • 82 pages • 2023
-
- $9.49
- + learn more
In [205]: from ets import load_boston 
import pandas as pd 
import numpy as np 
import seaborn as sns 
import t as plt 
import as sm 
from _selection import train_test_split 
from r_model import LinearRegression 
from er import KMeans 
from cs import mean_squared_error 
from ers_influence import variance_inflation_fac 
tor 
import math 
1.1. Read the data and do exploratory data analysis. Describe the data 
briefly. (Check the null values, Data types, shape, EDA). Perform 
Univariate and Bivari...
-
Chapter2-Econometrics-SimpleLinearRegressionAnalysis
- Summary • 41 pages • 2022
- Available in package deal
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- $4.49
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Chapter2-Econometrics-Simple Linear Regression Analysis
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Chapter6-Econometrics-RegressionAnalysisUnderLinearRestrictions
- Summary • 24 pages • 2022
- Available in package deal
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- $4.49
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Chapter6-Econometrics-Regression Analysis Under Linear Restrictions
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