As an independent statistical consultant, you have been contracted by Henry Oldman, a collector of grandfather clocks. Mr Oldman has observed auction sales of 32 grandfather clocks, collecting data...

Introduction
The variable to be predicted is the selling price of the clock. The variable on the basis of which predictions are made is age of the clock, expected bidders, and quality of the clock. I want to build a multiple regression model that can predict the selling price of Clock on the basis of its age, bidders, and quality.
Data
The variables which are measured by the ratio scale of measurement are the selling price of the clock, age of the clock, and expected bidders on the clock. The variable which is measured by the nominal scale of measurement is the quality of the clock. The quality of the clock is categorised as either good or normal. The good quality clock is coded as 1 and the normal quality clock is coded as 0.
Analysis
The dependent variable is the selling price which is plotted on the y-axis. The independent variables are the age of the clock, the number of Bidders on the clock and the quality of the clock. The independent variables are plotted on the x-axis in the scatter plot. The three-scatter plot is given below.

There is a strong positive linear relationship between the age of the clock and its selling price. An upward trend with all points close to each other is an indication for the same. With an increase in the age of the clock, the selling price increases drastically
There is a moderate positive linear relationship between the number of bidders on the clock and its selling price. An upward trend with all points moderately close to each other is an indication for the same. With an increase in the bidders on the clock, the selling price also increases.
The box plot for price bidders and age is given below. The box plot is plotted for the variables which are measured by the ratio scale of measurement.
There are no significant outliers in the data set. The middle line of the box in the box plot indicates that the distribution for all the three variables is approximately normal.
The multiple Regression model is given by:  selling price = -1284.2193 + 12.6208*age + 85.7962*bidders + 124.0003*quality
    Regression Analysis
    
    
    Regression Statistics
    Multiple R
    0.9537
    R Square
    0.9095
    Adjusted R Square
    0.8998
    Standard Error
    126.8486
    Observations
    32
    ANOVA
    
    
    
    
    
     
    df
    SS
    MS
    F
    Significance F
    Regression
    3
    4529864.1646
    1509954.7215
    93.8410
    0.0000
    Residual
    28
    450535.8354
    16090.5656
    
    
    Total
    31
    4980400.0000
     
     
     
     
    Coefficients
    Standard Error
    t Stat
    P-value
    Lower 95%
    Upper 95%
    Intercept
    -1284.2193
    165.2268
    -7.7725
    0.0000
    -1622.6710
    -945.7676
    Age
    12.6208
    0.8684
    14.5336
    0.0000
    10.8420
    14.3996
    Bidders
    85.7962
    8.3032
    10.3329
    0.0000
    68.7878
    102.8046
    Quality
    124.0003
    45.6578
    2.7159
    0.0112
    30.4745
    217.5261
With 1 year an increase in age of the clock, the price of the clock is increased by $12.6208. with...