Summary Statistics

  1. Numeric Features
    a d e
    count 3.0 4.0 4.0
    mean 2.0 230.25 302.25
    std 1.0 179.288176 127.335188
    min 1.0 42.0 123.0
    25% 1.5 102.75 271.5
    50% 2.0 223.5 331.5
    75% 2.5 351.0 362.25
    max 3.0 432.0 423.0
    number of nan 1.0 0.0 0.0
    Shprio Wilk p value 1.0 0.669265 0.450092
    Anderson Darling result is not from a normal distribution at 0.05 is from a normal distribution at 0.05 is from a normal distribution at 0.05
    data type float64 int64 int64
  2. Categorical Features
    b
    count 3
    unique 3
    top q
    freq 1
    number of nan 1
    unique values 'q': 1, 'w': 1, 'e': 1
    data type object
  3. Date Time Features
    c
    count 3
    unique 3
    latest date time 2020-03-03 00:00:00
    earliest date time 2020-03-03 00:00:00
    date time range 3682 days 00:00:00
    number of nan 1
    data type datetime64[ns]
  4. Outlier Records of Feature e
    a b c d e modified_z_score
    0 1.0 q 2010-02-02 42 123 -6.061135
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Exploratory Data Analysis

  1. Heatmap of Correlation Matrix
    EDA Visual
  2. Heatmap of Missing Values
    EDA Visual
  3. Q-Q Plot of Feature a
    EDA Visual
  4. Q-Q Plot of Feature d
    EDA Visual
  5. Q-Q Plot of Feature e
    EDA Visual
  6. Lineplot On All Numeric Features Paired with Date Time Features
    EDA Visual
  7. Cluster Map On All Numeric Features
    EDA Visual
  8. Pairplot On All Numeric Features
    EDA Visual
  9. Countplot On All Categorical Features
    EDA Visual
  10. Boxplot On All Categorical Features Paired with Numeric Features
    EDA Visual
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Preliminary Regression Analysis

  1. Forward Selection
    Step Predictor Entered AIC BIC R-squared Adjusted R-sqaured Log-likelihood P-value F-test significance
    0 Intercept 27.718295 26.411442 0.0 0.0 -12.859148 0.319851 NaN
  2. Backward Selection
    Step Predictor Entered AIC BIC R-squared Adjusted R-sqaured Log-likelihood F-test significance
    0 Full Model -99.429788 -102.043493 1.0 NaN 51.714894 NaN
  3. All Possible Selection
    Index Predictors AIC BIC R-squared Adjusted R-sqaured Log-likelihood
    0 a -112.811870 -115.425575 1.0 NaN 58.405935
    1 d -110.900847 -113.514553 1.0 NaN 57.450423
    2 a + d -99.429788 -102.043493 1.0 NaN 51.714894
  4. Best Models
    Criterion Predictors AIC BIC R-squared Adjusted R-sqaured Log-likelihood
    Best AIC a -112.811870 -115.425575 1.0 NaN 58.405935
    Best BIC a -112.811870 -115.425575 1.0 NaN 58.405935
    Best R-squared a -112.811870 -115.425575 1.0 NaN 58.405935
    Best R-squared d -110.900847 -113.514553 1.0 NaN 57.450423
    Best R-squared a + d -99.429788 -102.043493 1.0 NaN 51.714894
    Best Log-likelihood a -112.811870 -115.425575 1.0 NaN 58.405935
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