idrissrasheed

# coding: utf-8

#Libraries
import scipy.stats as stat
import numpy as np
from __future__ import division
import math
import matplotlib.pyplot as plt
%matplotlib inline

idrissrasheed

# coding: utf-8

# In[1]:

#libraries
import scipy.stats as stat
import numpy as np
from __future__ import division
import math

idrissrasheed

# coding: utf-8

# In[1]:

#Import libraries
import scipy.stats as stat
import numpy as np
from __future__ import division
get_ipython().magic(u'matplotlib inline')

idrissrasheed

```python
#Import libraries
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
from __future__ import division
%matplotlib inline
```

idrissrasheed

library(tseries)
# Simulate Gaussian white noise, find the sample acf, and compare with theoretical acf
x <- rnorm(300, 0, 1)

# Calculate and plot sample acf
myacf = acf(x,plot=FALSE)


# Simulate from an MA(1) process, e.g. X_t = Z_t + .8 Z_{t-1}
y <- arima.sim(list(ma=1), n = 300, sd = 1)

idrissrasheed

---
title: "PSTAT 131 HW1"
author: "Idris Rasheed and Faraz Farooq"
date: "April 12, 2017"
output: pdf_document
---
###1
(a) Looking up customers of a company according to their profitability.

No. This is a simple accounting calculation. 

idrissrasheed

/* exercise 1 */
/* set library location */
LIBNAME "C:\Users\SSMS1301-14\Desktop\PSTAT 130 M17"
/* reads airport data with three variables*/ 
data work.airports;
   infile 'airports.dat';
   input @ 1 Code $3.
         @ 4 City $50.
         @54 Country $15.;
run;

idrissrasheed

#Import libraries
import numpy as np
import math as math
n = 10000
def Monte_Carlo(n):
    return np.mean(np.exp(np.random.uniform(0,1,n)))
print Monte_Carlo(n)

idrissrasheed

---
title: "Bitcoins Market"
author: "Idris Rasheed"
date: "August 12, 2017"
output: pdf_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

idrissrasheed

---
title: "Pima Indian Women Code"
author: "Idris Rasheed"
date: "August 12, 2017"
output: pdf_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```