Q2: Calculate the correlations among all possible combinations of variables using the following data and write your interpretations.
Note: You are advised to use EXCEL or any other software for the calculation of correlations.
| State | Urban No of Bank Offices | Urban Amount Credit | Urban Amount Deposit | Urban No of Accounts |
| ANDAMAN & NICOBAR ISLANDS | 31 | 10798.91 | 23009.661 | 300860 |
| ANDHRA PRADESH | 4254 | 1771561.22 | 1785273.21 | 56997520 |
| ARUNACHAL PRADESH | 71 | 18713.635 | 55093.574 | 620951 |
| ASSAM | 1164 | 321567.825 | 807884.938 | 15333369 |
| BIHAR | 3056 | 559501.655 | 1812236.67 | 42338127 |
| CHANDIGARH | 424 | 585840 | 549184 | 3364488 |
| CHHATTISGARH | 1284 | 599595.538 | 848908.706 | 15436631 |
| DADRA & NAGAR HAVELI | 35 | 9937.519 | 26367.337 | 488036 |
| DAMAN & DIU | 43 | 8227.23 | 36462.355 | 473049 |
| GOA | 397 | 126414.224 | 433800.37 | 3640393 |
| GUJARAT | 4831 | 3619277.92 | 4567644.04 | 60961143 |
| HARYANA | 2905 | 1446481.5 | 2226409.05 | 31466846 |
| HIMACHAL PRADESH | 381 | 90320.203 | 271842.575 | 2927090 |
| JAMMU & KASHMIR | 819 | 239474.898 | 578992.602 | 8568486 |
| JHARKHAND | 1501 | 385210.622 | 1302088.44 | 17698133 |
| KARNATAKA | 6204 | 4337559.3 | 6418221.89 | 72858087 |
| KERALA | 5949 | 2212958.59 | 3575806.38 | 59406050 |
| LAKSHADWEEP | 5 | 413.064 | 4906.115 | 34583 |
| MADHYA PRADESH | 3901 | 1447929.15 | 2508450.77 | 56132871 |
| MAHARASHTRA | 8846 | 21914275.1 | 21203097.7 | 139566919 |
| MANIPUR | 84 | 17502.179 | 47232.768 | 1216224 |
| MEGHALAYA | 165 | 30045.858 | 141589.032 | 1134644 |
| MIZORAM | 102 | 20101.754 | 51840.488 | 743615 |
| NAGALAND | 102 | 21505.157 | 70089.604 | 871327 |
| NCT OF DELHI | 3408 | 9559956.37 | 9604406.95 | 43749602 |
| ODISHA | 2123 | 678962.946 | 1608027.32 | 21675814 |
| PUDUCHERRY | 180 | 75818.599 | 118598.454 | 1989219 |
| PUNJAB | 3681 | 1547952.7 | 2283001.19 | 35795072 |
| RAJASTHAN | 3988 | 1475735.94 | 2194328.32 | 45786526 |
| SIKKIM | 39 | 10980.099 | 42445.246 | 303941 |
| TAMIL NADU | 7218 | 6172405.9 | 5455337.41 | 89424694 |
| TELANGANA | 3296 | 3359268.45 | 3303802.62 | 43319782 |
| TRIPURA | 216 | 41708.593 | 127616.832 | 2685808 |
| UTTAR PRADESH | 8522 | 2490881.56 | 5930432.61 | 117339360 |
| UTTARAKHAND | 1042 | 251706.35 | 748447.406 | 8992680 |
| WEST BENGAL | 4498 | 3061581 | 5141434.75 | 65921120 |
SOLUTION:
To calculate the correlations among all possible combinations of variables, we need data for each variable in the dataset. From the provided data, it seems that we have data for the following variables:
- State
- Urban No of Bank Offices
- Urban Amount Credit
- Urban Amount Deposit
- Urban No of Accounts
To calculate the correlations, we can use the following steps:
Step 1: Prepare the data Organize the data into a table or a spreadsheet, where each variable represents a column, and each observation represents a row. Make sure that each variable has numerical values.
Step 2: Calculate the correlation coefficient Use a statistical software or a spreadsheet program that supports correlation calculations (e.g., Excel, Python with NumPy or pandas, R) to calculate the correlation coefficient between each pair of variables. The correlation coefficient measures the strength and direction of the linear relationship between two variables.
Step 3: Interpret the correlations Interpret the correlations based on their values, which range from -1 to 1:
- A correlation coefficient of 1 indicates a perfect positive linear relationship. As one variable increases, the other variable also increases proportionally.
- A correlation coefficient of -1 indicates a perfect negative linear relationship. As one variable increases, the other variable decreases proportionally.
- A correlation coefficient close to 0 indicates a weak or no linear relationship. The variables may be independent of each other or have a nonlinear relationship.
Remember that correlation does not imply causation. Even if variables are strongly correlated, it does not necessarily mean that one variable causes changes in the other.
If you provide the specific values for each variable in the dataset, I can assist you further in calculating the correlations and providing interpretations.
Follow my youtube channel for details step by step calculation.
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