# Effects of investment environment on SME's gross capital formation in the Sub-Saharan region

# Load computational libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import r2_score

Abstract

### 1.Introduction

# 2 Literature Review

## 3. Methodology

## Data

## Methods

## 4.Data Pre-processing and Exploration

#STEP 2: Check all the columns in the data set to selct the required variables only
df.columns

## Regression Analysis

#STEP 6: Exploratory data analysis.
# We split the dataset in order to obtain two different set that are used for training and validation of the regression equation
x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=0.3, random_state=42)

#STEP 8: Predict the model
# we predict the value of y which is the response based on the seperated test data
y_prediction = model.predict(x_test)

# 6 Results and Discussion

#STEP 12 Summary Statistics
# We continue further on a summary statistics to determine the r2 with indicates how well the independent varibales affect the response variable
r2_score(y_train, model.predict(x_train))

# 7 Conclusion and Policy Recommendation

References