Hi Excel experts,
I'm trying to run a linear regression on two columns with integers as values after filtering them for blanks (missing values) and after filtering the rows based on "yes"/"no" values of another column in the table.
When I run the regression, I get the following error:
Regression - LINEST() Function Error
Question:
1. How can I temporarily filter out the entire rows for which there are no values in a cell within that row?
2. How can I deal with this error in order to run the regression?
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Thank you in advance.
Lee
I'm trying to run a linear regression on two columns with integers as values after filtering them for blanks (missing values) and after filtering the rows based on "yes"/"no" values of another column in the table.
When I run the regression, I get the following error:
Regression - LINEST() Function Error
Question:
1. How can I temporarily filter out the entire rows for which there are no values in a cell within that row?
2. How can I deal with this error in order to run the regression?
ID | Q1 | Q3 | Q4 |
1 | 1 | 3 | Y |
2 | 5 | 4 | Y |
4 | 2 | 2 | Y |
5 | 4 | 2 | Y |
6 | 3 | 2 | Y |
7 | 1 | 2 | Y |
8 | 1 | 2 | Y |
9 | 1 | 2 | Y |
10 | 1 | 2 | Y |
11 | 1 | 1 | Y |
12 | 5 | 4 | Y |
13 | 2 | 2 | Y |
14 | 1 | 2 | Y |
15 | 5 | 2 | Y |
17 | 2 | 2 | Y |
18 | 1 | 2 | Y |
31 | 2 | 3 | Y |
34 | 1 | 2 | Y |
38 | 1 | 1 | Y |
39 | 2 | 1 | Y |
40 | 2 | 1 | Y |
41 | 2 | 2 | Y |
42 | 2 | 2 | Y |
43 | 4 | 1 | Y |
44 | 2 | 1 | Y |
45 | 1 | Y | |
46 | 2 | 2 | Y |
48 | 4 | 1 | Y |
49 | 1 | Y | |
50 | 2 | 1 | Y |
51 | 2 | 1 | Y |
52 | 2 | 3 | Y |
53 | 2 | 2 | Y |
54 | 1 | 1 | Y |
55 | 1 | 2 | Y |
56 | 1 | Y | |
57 | 1 | 2 | Y |
60 | 1 | 1 | Y |
61 | 2 | 1 | Y |
62 | 3 | 2 | Y |
65 | 4 | 2 | Y |
66 | 1 | 2 | Y |
67 | 3 | 3 | Y |
68 | 1 | 3 | Y |
69 | 1 | 2 | Y |
70 | 2 | 2 | Y |
71 | 2 | 2 | Y |
72 | 2 | 2 | Y |
74 | 2 | 2 | Y |
76 | 1 | 1 | Y |
77 | 2 | 2 | Y |
78 | 1 | 2 | Y |
80 | 2 | 1 | Y |
81 | 3 | 2 | Y |
82 | 3 | 2 | Y |
83 | 1 | 2 | Y |
85 | 2 | 2 | Y |
86 | 3 | 2 | Y |
87 | 2 | 2 | Y |
88 | 4 | 2 | Y |
89 | 3 | 2 | Y |
90 | 2 | 1 | Y |
94 | 2 | 2 | Y |
95 | 2 | 2 | Y |
96 | 2 | 2 | Y |
97 | 3 | 2 | Y |
98 | 3 | 2 | Y |
100 | 1 | 3 | Y |
101 | 2 | 1 | Y |
102 | 1 | 1 | Y |
103 | 3 | 2 | Y |
104 | 1 | 2 | Y |
105 | 1 | 3 | Y |
107 | 1 | 2 | Y |
108 | 2 | 1 | Y |
110 | 1 | 2 | Y |
113 | 2 | 2 | Y |
114 | 1 | 3 | Y |
115 | 1 | 2 | Y |
119 | 1 | 3 | Y |
121 | 3 | 3 | Y |
123 | 1 | 1 | Y |
125 | 1 | 1 | Y |
126 | 3 | 1 | Y |
127 | 1 | 3 | Y |
128 | 2 | 1 | Y |
129 | 3 | 1 | Y |
130 | 1 | 1 | Y |
131 | 3 | 3 | Y |
134 | 1 | 2 | Y |
135 | 1 | Y | |
136 | 1 | 2 | Y |
138 | 2 | 1 | Y |
139 | 2 | Y | |
140 | 1 | Y | |
141 | 2 | 2 | Y |
142 | 2 | 2 | Y |
146 | 2 | 1 | Y |
147 | 4 | 2 | Y |
148 | 1 | 4 | Y |
151 | 1 | Y | |
152 | 4 | 3 | Y |
153 | 4 | 2 | Y |
154 | 1 | 2 | Y |
155 | 2 | 1 | Y |
156 | 1 | 2 | Y |
157 | 1 | 2 | Y |
158 | 1 | 2 | Y |
159 | 1 | 1 | Y |
160 | 1 | 2 | Y |
162 | 2 | 2 | Y |
163 | 2 | 2 | Y |
166 | 2 | 3 | Y |
168 | 1 | 2 | Y |
170 | 4 | 3 | Y |
174 | 3 | 2 | Y |
175 | 1 | 3 | Y |
176 | 1 | 3 | Y |
180 | 2 | 2 | Y |
181 | 2 | 2 | Y |
182 | 2 | 2 | Y |
183 | 1 | 2 | Y |
184 | 1 | 3 | Y |
185 | 2 | 3 | Y |
188 | 3 | 4 | Y |
189 | 2 | 3 | Y |
191 | 4 | 1 | Y |
193 | 2 | 1 | Y |
195 | 1 | 1 | Y |
202 | 1 | 1 | Y |
203 | 3 | 3 | Y |
204 | 1 | 2 | Y |
205 | 5 | 2 | Y |
206 | 1 | 2 | Y |
207 | 1 | 2 | Y |
208 | 1 | 2 | Y |
210 | 2 | 1 | Y |
211 | 2 | 1 | Y |
213 | 2 | 2 | Y |
221 | 1 | 2 | Y |
222 | 1 | 2 | Y |
225 | 1 | 4 | Y |
227 | 3 | 2 | Y |
228 | 1 | 3 | Y |
229 | 3 | 2 | Y |
232 | 1 | 2 | Y |
233 | 1 | 2 | Y |
235 | 1 | 3 | Y |
237 | 3 | 2 | Y |
238 | 4 | 1 | Y |
239 | 2 | 1 | Y |
241 | 1 | 1 | Y |
242 | 3 | 2 | Y |
<tbody>
</tbody><colgroup><col><col span="3"></colgroup>
Thank you in advance.
Lee