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asiedu opoku
Добавлен 14 дек 2012
Deeper life Campus Fellowship KNUST
Bringing life and hope to intellectuals
Bringing life and hope to intellectuals
Regression analysis on categorical variable in Python
Python is an exceptional tool in determining the statistical relationship between independent categorical variable in multiple regression analysis
Просмотров: 14 268
Видео
Regression Analysis in Python
Просмотров 554 года назад
Regression Analysis is statistical estimation of the relationship between one or more independent variable and an dependent variable
Post Hoc Analysis
Просмотров 284 года назад
Post Hoc Analysis is perform to confirm where the differences occurred between groups after a ANOVA test result.
How to Perform one-way ANOVA in python
Просмотров 5934 года назад
One-way ANOVA is used to determine whether there are statistically significant differences between means of 3 or more independent (unrelated) groups and python is excellent for data analysis
How to use Python to plot Boxplot
Просмотров 4624 года назад
Boxplot is the standardized way of displaying the distribution of data based on a five number summary; minimum, First quartile, median, third quartile, maximum, outlier. Python is also an excellent tool which can be used to make amazing boxplots
Deeper life National Campus Congress : CONQUERORS 2017
Просмотров 3027 лет назад
This programme is designed for students and staff of all tertiary institutions including national service persons and intending ones. There are two venues for this programme, one is situated at Anyaa, Accra and the other at Brofoyedru, Kumasi.
even the ols giving error saying variable required
Hey, I have more than two variables such as material_con, material_timber, material_others, Design_slab,Design_flat,Design_rec but there is an error after dropping the data can you help here do you have any video on more than 2 variable??
P-value for female variable indicates that it is not significant for a model (since it is 0.39, but the significance level is usually 0.05)
xan this be directly used for factorial anova
Cc
thanks man
Thank you for this. How can one handle multiple categorical variables? For e.g. If you have more than one column of categorical variable with some of them having more than 2 possible results e.g size: large, medium and small, how do I handle this? I used the get.dummies function to convert to binary but I'm now stuck
df= pd.get_dummies(df, columns=['var1','var2','var3',....'varn'], prefix='', prefix_sep='') df.head()
did you solved it ?
Last code is not running
well and simply done!
SO helpful
Thanks. Very helpful video!
Thank you so much!
Bro you are awesome
thanks! this pretty straightforward no useless information, keep it up
Isn't male and female binary data and wouldn't be a logistic regression model be better?
Don't think so since the output of a logistic model would be a categorical variable. So since you are predicting price this can't use logistic regression.
I am anticipating this programme, Conquerors 2017. God bless